FEDERAL LAND MANAGERS’ 

AIR QUALITY RELATED VALUES 

WORKGROUP (FLAG) 

PHASE I REPORT 

(December 2000) 

U.S. FOREST SERVICE – AIR QUALITY PROGRAM 

NATIONAL PARK SERVICE – AIR RESOURCES DIVISION 

U.S. FISH AND WILDLIFE SERVICE – AIR QUALITY BRANCH 

Table of Contents 

A. EXECUTIVE SUMMARY .............................................................................................................iii 

1. RECOMMENDATIONS FOR EVALUATING VISIBILITY IMPACTS .........................iv 

2. RECOMMENDATIONS FOR EVALUATING OZONE IMPACTS.................................vii 

3. RECOMMENDATIONS FOR EVALUATING DEPOSITION IMPACTS .......................ix 

B. BACKGROUND ...............................................................................................................................1 

1. HISTORY ....................................................................................................................................1 

a. FLAG Approach .....................................................................................................................1 

b. FLAG Organization................................................................................................................2 

2. OVERVIEW OF RESOURCE ISSUES....................................................................................2 

a. Visibility..................................................................................................................................3 

b. Vegetation ...............................................................................................................................3 

c. Soils and Surface Waters........................................................................................................4 

3. LEGAL RESPONSIBILITIES ..................................................................................................4 

4. COMMONALITIES AMONG FEDERAL LAND MANAGERS..........................................5 

a. Identifying AQRVs ................................................................................................................6 

b. Determining the Levels of Pollution that Trigger Concern for the Well-Being 

 of AQRVs................................................................................................................................6 

c. Visibility..................................................................................................................................6 

d. Biological and Physical Effects..............................................................................................6 

e. Determining the Level of Pollution Likely to Cause an “Adverse Impact” 

 on AQRVs...............................................................................................................................7 

f. FLM Databases ......................................................................................................................7

C. FEDERAL LAND MANAGERS' APPROACH TO AQRV PROTECTION................................8 

 1. AQRV PROTECTION AND IDENTIFICATION...................................................................8 

 2. NEW SOURCE REVIEW ...................................................................................................8 

a. Roles and Responsibilities of FLMs .....................................................................................9 

b. Elements of Permit Review .................................................................................................10 

c. FLM Permit Review Process ..............................................................................................13 

d. Criteria for Decision Making (Adverse Impact Considerations)........................................15 

e. Air Pollution Permit Conditions that Benefit Class I Areas ................................................16 

f. Reducing Pollution in Nonattainment Areas (Nonattainment Permit Process) ................17 

 3. OTHER AIR QUALITY REVIEW CONSIDERATIONS ...................................................17 

a. Remedying Existing Adverse Impacts.................................................................................18 

b. Requesting SIP Revisions to Address AQRV Adverse Impacts .......................................18 

c. Periodic Increment Consumption Review ..........................................................................19 

 4. MANAGING EMISSIONS GENERATED IN AND NEAR FLM AREAS........................20 

a. Prescribed Fire ......................................................................................................................20 

b. Strategies to Minimize Emissions from Sources In and Near FLM Areas........................21 

c. Conformity Requirements in Nonattainment Areas............................................................23 

D. SUBGROUP REPORTS: TECHNICAL ANALYSES AND RECOMMENDATIONS...........24 

 1. SUBGROUP OBJECTIVES AND TASKS ............................................................................24 

 2. VISIBILITY...............................................................................................................................24 

 a. Introduction...........................................................................................................................24 

 b. Analysis Techniques.............................................................................................................29 

 c. Air Quality Models and Visibility Assessment Procedures................................................29 

 d. Summary ...............................................................................................................................35 
ii 

 e. Appendix 2.A Visibility Parameters ..................................................................................36 

 f. Appendix 2.B Estimate of Natural Conditions...................................................................40 

 g. Appendix 2.C Example Problem ........................................................................................69 

 3. OZONE .....................................................................................................................................75 

a. Introduction...........................................................................................................................75 

b. Ozone Effects on Vegetation ...............................................................................................75 

c. Recommended Metric to Determine Phytotoxic Ozone Concentrations ..........................77 

d. Identification of Ozone Sensitive AQRVs or Sensitive Receptors ...................................79 

e. Review Process for Sources that Could Affect Ozone Levels or Vegetation in 

 FLM Areas ...........................................................................................................................79 

 f. Further Guidance to FLMs ............................................................................................82 

g. Ozone Air Pollution Websites.......................................................................................83 

h. Appendix 3.A A Preliminary Listing for Selected USDA/FS, NPS, and FWS 

 Class I Areas of Plant Species that have been Shown to be Sensitive Receptors 

 for Ozone...............................................................................................................................84 

 i. Appendix 3.B List of Representative Low and High W126 and N100 Values 

 for SELECTED NPS and FWS Areas.........................................................................103 

4. DEPOSITION..........................................................................................................................119 

a. Introduction.........................................................................................................................119 

b. Current Trends in Deposition.............................................................................................120

c. Identification and Assessment of AQRVs.........................................................................125 

d. Determining Critical Loads ...............................................................................................129 

e. Other AQRV Identification and Assessment Tools..........................................................132 

f. Recommendations and Guidance for Evaluating Potential Effects from 

 Proposed Increases in Deposition to an FLM Area .........................................................134 

g. Summary .............................................................................................................................142 

h. Websites for Deposition and Related Information............................................................143 

E. FUTURE FLAG WORK .......................................................................................................151 

1. IMPLEMENTING FLAG RECOMMENDATIONS...........................................................151 

2. PHASE I UPDATES...............................................................................................................151 

3. PHASE II TASKS...................................................................................................................151 

APPENDIXES 

A. GLOSSARY ..................................................................................................................................152 

B. LEGAL FRAMEWORK FOR MANAGING AIR QUALITY AND 

 AIR QUALITY EFFECTS ON FEDERAL LANDS .................................................................157 

C. GENERAL POLICY FOR MANAGING AIR QUALITY RELATED 

 VALUES IN CLASS I AREAS....................................................................................................166

D. BEST AVAILABLE CONTROL TECHNOLOGY (BACT) ANALYSIS ..........................168 

E. MAPS OF FEDERAL CLASS I AREAS..............................................................................169 

F. CLASS I AREA CONTACTS......................................................................................................173 

G. FLAG PARTICIPANTS ..............................................................................................................195 

H. BIBLIOGRAPHY..........................................................................................................................199 
iii 

A. EXECUTIVE SUMMARY 

The Federal Land Managers' Air Quality Related Values Work Group (FLAG) was formed to develop 

a more consistent approach for the Federal Land Managers (FLMs) to evaluate air pollution effects on 

their resources. Of particular importance is the New Source Review (NSR) program, especially in the 

review of Prevention of Significant Deterioration (PSD) of air quality permit applications. The goals 

of FLAG have been to provide consistent policies and processes both for identifying air quality related 

values (AQRVs) and for evaluating the effects of air pollution on AQRVs, primarily those in Federal 

Class I air quality areas, but in some instances, in Class II areas. Federal Class I areas are defined in 

the Clean Air Act as national parks over 6,000 acres and wilderness areas and memorial parks over 

5,000 acres, established as of 1977. All other FLM areas are designated Class II. Maps of Federal 

Class I areas are provided in Appendix E. Lists of Class I Area contacts are provided in Appendix F. 

FLAG members include representatives from the three FLMs that administer the nation's Federal 

Class I areas: the U.S. Department of Agriculture Forest Service (USDA/FS), the National Park 

Service (NPS), and the U.S. Fish and Wildlife Service (FWS). (Subsequently in this report, these 

three agencies collectively will be referred to as “FLMs.” Class I and Class II air quality areas are 

called "FLM areas" in this report.) Appendix G contains a list of FLAG Participants. 

This report describes the work accomplished in Phase I of the FLAG effort. That work includes 

identifying policies and processes common to the FLMs (herein called “commonalities”) and 

developing new policies and processes using readily available information. This report provides 

State permitting authorities and potential permit applicants a consistent and predictable process for 

assessing the impacts of new and existing sources on AQRVs, including a process to identify those 

AQRVs and potential adverse impacts. The report also discusses non-new source review 

considerations and managing emissions in Federal areas. In Phase II, FLAG will address 

unresolved issues including those that will require research and the collection of new data. 

This FLAG Phase I Report consolidates the results of the FLAG Visibility, Ozone, and Deposition 

subgroups. The chapters prepared by these subgroups contain issue-specific technical and policy 

analyses, recommendations for evaluating AQRVs, and guidelines for completing and evaluating 

NSR permit applications. These recommendations and guidelines are intended for use by the 

FLMs, permitting authorities, NSR permit applicants, and other interested parties. The report 

includes background information on the roles and responsibilities of the FLMs under the NSR 

program. 

This document includes guidelines for completing and evaluating NSR applications that may affect 

FLM areas. It does not provide a universal formula that would, in all situations, allow one to 

determine whether or not a source of air pollution does, or would, cause or contribute to an adverse 

impact. That determination remains a project-specific management decision, the responsibility for 

which remains with the FLM, as delegated by Congress. The FLM's assessment of whether or not an 

adverse impact would occur is based on the sensitivity of the AQRVs at the particular FLM area under 

consideration. 

To provide information for the FLM’s assessment of adverse impacts on AQRVs, the permit applicant 

should identify the potential impacts of the source on all applicable AQRVs of that area. An FLM 
iv 

may ask that an applicant address any or all of the areas of concern. The primary areas of concern to 

the FLMs with respect to air pollution emissions are visibility impairment, ozone effects on 

vegetation, and effects of pollutant deposition on soils and surface waters. 

The FLAG Phase I Report also describes the FLAG effort–including the FLAG approach, 

organization, and plans for future FLAG work. Appendix A of the report contains a glossary of 

technical terms, abbreviations, and acronyms used in the report along with associated definitions. 

Appendix H provides a list of all references cited in the FLAG report. 

The key recommendations developed by the Visibility, Ozone, and Deposition subgroups are 

summarized below. However, for all three subject matter areas, FLAG recommends that the permit 

applicant consult with the appropriate regulatory agency and with the FLM for the affected area(s) for 

confirmation of preferred procedures. This consultation should take place in the early stages of the 

permit application process. 

1. RECOMMENDATIONS FOR EVALUATING VISIBILITY IMPACTS 

FLAG has provided guidance in the form of recommendations, specific prescriptions, and 

interpretation of results for assessing visibility impacts of sources near Class I areas (although this 

guidance is generally applicable to Class II areas, as well). The guidance addresses assessments for 

sources proposed for locations near (generally within 50 km) and at large distances (greater than 50 

km) from these areas. It also recommends impairment thresholds and identifies the conditions for 

which cumulative analyses of all increment-consuming sources would be necessary. The key 

components of the recommendations are highlighted below. 

In general, FLAG recommends that an applicant: 

• Consult with the appropriate regulatory agency and with the FLM for the affected Class I area(s) 

or other affected area for confirmation of preferred procedures and for the need for a cumulative 

analysis. 

• Obtain FLM recommendation for the specified reference levels (estimate of natural conditions) 

and, if applicable, FLM recommended plume/observer geometries and model receptor locations. 

• Apply the applicable EPA Guideline, steady-state models for regions within the Class I area that 

are affected by plumes or layers that are viewed against a background (generally within 50 km of 

the source). 

Calculate hourly estimates of ∆E and plume contrast, with respect to natural conditions, and 

compare these estimates with the thresholds given in Section D.2.c. 

• For regions of the Class I area where visibility impairment from the source would cause a general 

alteration of the appearance of the scene (generally 50 km or more away from the source or from 

the interaction of the emissions from multiple sources), apply a non-steady-state air quality model 

with chemical transformation capabilities (refer to IWAQM guidance documents), which yields 

ambient concentrations of visibility-impairing pollutants. At each Class I receptor: 
v 

Calculate the change in extinction due to the source being analyzed, compare these changes 

with the reference conditions, and compare these results with the thresholds given in Section 

D.2.c. 

If necessary, calculate the cumulative change in extinction due to new source growth. 

This prescription is portrayed schematically in Figure V-1. 
vi 

Figure V-1. Prescription for visibility assessment for distant/multi-source applications 

(source greater than or equal to 50 km from the Class I area) 

Prescription for New Source 

Review Visibility Analysis 

(Distant/Multi-source) 

Single-source 

contribution to 

change in 

extinction ≥

10.0% 

?

FLM likely to object 

to the permit 

FLM not likely to 

object to the permit 

Has a cumulative analysis been 

conducted (or has the source 

triggered a need for a cumulative 

impact analysis) or is its 

contribution to extinction ≥ 5.0% 

 ?

Conduct cumulative 

visibility analysis of PSD 

increment consuming 

sources 

Cumulative change in 

extinction ≥10% and 

single-source 

contribution ≥ 0.4% 

? 

FLM likely to object 

to the permit 

Yes

No 

No 

Yes

Yes

No 
vii 

2. RECOMMENDATIONS FOR EVALUATING OZONE IMPACTS 

• FLAG agrees with the EPA contention that single source-receptor modeling for ozone is not 

feasible at this time. FLM actions or specific requests on a permit application will be based on 

the existing air pollution situation at the area they manage. These conditions include (1) 

whether or not actual ozone damage has occurred in the area, and (2) whether or not ozone 

exposure levels occurring in the area are high enough to cause damage to vegetation (i.e.,

phytotoxic O3 exposures). Figure O-1 shows the various responses an FLM would have to a 

permit application. (Note: the term “Ozone exposure currently recognized as phytotoxic” is 

determined based on data from exposure response studies and ambient ozone levels at the site. 

The FLM may ask the applicant to calculate the ozone exposure values if these data are not 

already available. “Ozone damage to vegetation” is determined from field observations at the 

impacted site.) 

• Oxidant stipple necrosis on plant foliage and ozone-induced senescence infer adverse 

physiological or ecological effects, and are considered to be damage if they are determined to 

have a negative impact on aesthetic value. 

• The W126 ozone metric is recommended to describe ozone exposure, based on a 24-hour, 

seasonal (April through October) period of measurement. The number of hours in this period of 

time greater than or equal to 100 ppb (N100) will also be determined, in recognition of the 

importance of peak concentrations in plant response. 

• NOx and VOC are of concern because they are precursors of ozone. Current information indicates 

most FLM areas are NOx limited. Until we determine the VOC or NOx status of each area, we will 

focus on control of NOx emission sources. 
viii 

Figure O-1. FLM response to potential ozone effects from new emissions source. 

 

 No 

 

 Unknown Unknown Yes 

 

 

 Yes 

 No 

 

 

 Unknown Yes

 

 

 No 

 

Items referenced in Figure O-1: 

a. The FLM may recommend one or more of the following: 

- That the proposed source use stricter than BACT controls (e.g., Lowest Achievable Emission 

Rate [LAER]). 

- That the proposed source obtain NOx emission offsets that will benefit the potentially affected 

FLM area (as demonstrated by dispersion modeling). 

- That the permitting authority (i.e., state or EPA) conduct regional modeling to identify sources 

that are contributing significantly to ozone-associated impacts in the FLM area, and that the 

permitting authority then undertake actions necessary to reduce emissions from those sources (e.g., 

SIP revision). 

b. The applicant calculate the ozone exposure for vegetation (using W126 and N100 metrics) for the 

affected FLM area(s) where such information is not already available. 

c. The permitting authority or applicant fund post-construction ambient ozone monitoring in or near 

the FLM area. 

d. The applicant conduct or fund post-construction ozone effects surveys in the FLM area and/or 

exposure/response effects research. 

a

FLM not likely to 

object to permit,; 

FLM may ask for d

FLM not likely 

to object to permit 

Ozone 

damage to 

vegetation

FLM not likely 

to object to 

permit; FLM 

may ask for 

c and/or d

a; FLM may ask for c

FLM not likely to 

object to permit; 

FLM may ask for c

START 

Ozone 

damage to 

vegetation a

Ozone

exposure

currently

recognized as

phytotoxic ; FLM

may ask for b
ix 

3. RECOMMENDATIONS FOR EVALUATING DEPOSITION IMPACTS 

The permit applicant should consult with the appropriate regulatory agency and FLM for the affected 

area(s) to determine if a deposition impact analysis should be done. If an analysis is advised, the 

permit applicant should obtain available information on Class I AQRVs, critical loads, and concern 

thresholds from the FLM. In addition, the applicant should refer to the “Recommendations and 

Guidance for Evaluating Potential Effects from Proposed Increases in Deposition to an FLM Area” 

section of the Deposition Chapter (Section D.4.f). The following steps summarize that guidance. 

• Estimate the current deposition rate to the FLM area. A list of monitoring sites providing data to 

characterize deposition in FLM areas is included in the Deposition Chapter (Table D-2). 

• Estimate the future deposition rate by adding the existing rate, the new emissions’ contribution to 

deposition, and the contribution of sources permitted but not yet operating. Modeling of new and 

permitted but not yet operating emissions’ contribution to deposition should be conducted 

following IWAQM recommendations. 

• Compare the future deposition rate with the recommended screening criteria (e.g., critical load, 

concern threshold, or screening level value) for the affected FLM area. A list of documents 

summarizing these screening criteria, where available, can be found in Appendix H. Information 

for USDA/FS Class I areas is also available at: 

http://www.fs.fed.us/r6/aq/natarm. 

 A website with NPS and FWS Class I area information is currently under development. 

• In consultation with the FLM, use the following flowchart (Figure D-1) to determine whether 

mitigation is recommended. 
x 

No/Unknown

Yes

START

Current

 adverse 

effects to AQRVs

from deposition/

Critical load 

exceeded

?

Yes

Unknown

No

New 

emissions 

cause or contribute to 

adverse effects/Critical

 load exceeded

?

FLM may recommend

elements of "a" or "b"

or (if necessary) "c"

 a. The applicant should use one or more of the following:

 - Stricter (than BACT) controls (e.g., Lowest Achievable Emission Rate [LAER]).

 - Emission offsets located in an area that, considering geographic and meteorological

 factors, will benefit the impacted wilderness or park, as demostrated by modeling.

 - Regional modeling to identify sources contributing significantly to deposition 

 adverse effects; SIP revision to reduce emissions contributing to adverse effects.

 (See text for discussion of mitigation options.) 

 b. Deposition and deposition effects monitoring/research in the FLM area.

 c. Denial of permit.

FLM unlikely

 to object to permit

FLM unlikely to

object to permit;

may recommend "b"

Figure D-1. FLM resonse to potential deposition effects from new 

emissions sources.

Figure D-1. FLM response to potential deposition effects from new 

emissions sources.
B. BACKGROUND 

1. HISTORY 

The Clean Air Act Amendments of 1977 give Federal Land Managers (FLMs) an “affirmative 

responsibility” to protect the natural and cultural resources of Class I areas from the adverse 

impacts of air pollution. (See Appendix B. “LEGAL FRAMEWORK FOR MANAGING AIR 

QUALITY AND AIR QUALITY EFFECTS ON FEDERAL LANDS.”) FLM responsibilities 

include the review of air quality permit applications from proposed new or modified major 

pollution sources near these Class I areas. If, in its permit review, an FLM demonstrates that 

emissions from a proposed source will cause or contribute to adverse impacts on the air quality 

related values (AQRVs) of a Class I area, the permitting authority, typically the State, can deny the 

permit. 

Individually, FLMs have developed different approaches to identifying AQRVs and defining 

adverse impacts on AQRVs in Class I areas. For example, in 1988, the U.S. Department of 

Agriculture Forest Service (USDA/FS) conducted a national screening process to identify the 

AQRVs for each of its Class I areas. Using this national process as a starting point, each USDA/FS 

region refined the screening parameters and identified sensitive AQRVs for many Class I areas. 

However, this resulted in differences in the approaches and levels used by USDA/FS regions. The 

U.S. Department of the Interior National Park Service (NPS) and the U.S. Fish and Wildlife 

Service (FWS) have adopted a case-by-case approach to permit review, considering the most recent 

information available for each area. NPS and FWS have not completed lists of sensitive AQRVs 

nor defined adverse impact levels for all of their Class I areas. 

a. FLAG Approach 

Air resource managers from the USDA/FS, NPS, and FWS recognized the need for a more 

consistent approach among their agencies with respect to their efforts to protect AQRVs. In April 

1997, an interagency workgroup was formed whose objective was “to achieve greater consistency 

in the procedures each agency uses in identifying and evaluating AQRVs.” The workgroup named 

itself the Federal Land Managers' Air Quality Related Values Work Group, or FLAG. Although 

FLAG membership comprises air resource managers and subject matter experts from the three 

agencies, representatives from the U.S. Environmental Protection Agency (EPA), U.S. Geological 

Survey, and State air agencies have also participated in FLAG efforts. 

FLAG participants have collaborated to: 

• define sensitive AQRVs, 

• identify the critical loads (or pollutant levels) that would protect an area and identify the 

criteria that define adverse impacts, and 

• standardize the methods and procedures for conducting AQRV analyses. 

To accomplish its objective, FLAG started with (and will continue to build on) the procedures, 

terms, definitions, and screening levels common to the three agencies. Many such 

“commonalities” were identified early in the FLAG planning sessions. (See section B.4. 

“COMMONALITIES AMONG FEDERAL LAND MANAGERS.”) 
2 

FLAG’s “Action Plan” stipulates a phased approach. Phase I addressed issues that could be resolved 

without research or the collection of new data. Phase II will address the more complex and unresolved 

issues from Phase I that may require additional data collection. (See section E. “FUTURE FLAG 

WORK.”) 

The FLAG effort focuses on the effects of the air pollutants that could affect the health of resources 

in Class I areas, primarily pollutants such as ozone, particulate matter, nitrogen dioxide, sulfur 

dioxide, nitrates, and sulfates. In Phase I, FLAG concentrated on four issues: (1) terrestrial effects 

of ozone; (2) aquatic and terrestrial effects of wet and dry pollutant deposition; (3) visibility 

impairment; and (4) process and policy issues. Four subgroups, one for each of these issues, were 

formed and charged with developing a set of recommendations for consistent policies and 

processes. 

In Phase I, FLAG findings and technical recommendations underwent scientific peer review, as 

well as review by agency decisionmakers such as Class I area Park Superintendents, Refuge 

Managers, and Forest Supervisors; Regional Foresters; and the Assistant Secretary for Fish and 

Wildlife and Parks. (Note: USDA/FS has designated the FLM as the Regional Foresters and, in 

some cases, Forest Supervisors. However, the Assistant Secretary for Fish and Wildlife and Parks 

holds FLM responsibilities for NPS and FWS.) FLAG products have also undergone public review 

and comment. [A “notice of availability” of the draft FLAG report was published in the Federal 

Register, and the FLMs conducted a public meeting to discuss the draft FLAG report and provided 

a 90-day public comment period.]

b. FLAG Organization 

In addition to the four subgroups (policy, deposition, ozone, and visibility), the FLAG organization 

included Leadership and Coordinating Committees and a Project Manager. The Leadership 

Committee, which includes the air quality program chiefs from the three FLM agencies, was 

responsible for providing direction to the workgroup and the resources necessary for FLAG to 

accomplish its objective. The Coordinating Committee, which also includes representatives from 

each agency, was responsible for communications within the workgroup, including coordination 

among the agencies and subgroups. The FLAG Project Manager coordinated FLAG activities, 

served as a single point-of-contact for the subgroups, and performed other administrative functions. 

2. OVERVIEW OF RESOURCE ISSUES 

 

Research conducted on Federal lands by FLMs and others has characterized natural resource effects 

associated with air pollution, and has helped identify those particular resources that are vulnerable to 

pollution. This effort does not address the impacts from air pollution on cultural resources. 

Documented effects include impairment of visibility, injury and reduced growth of vegetation, and 

acidification and fertilization of soils and surface waters. Air pollution effects on resources have been 

identified in a number of FLM areas; a few examples are provided below. It is important to note that 

similar, or even more serious, air pollution effects may be occurring on all Federal lands, but FLMs 

have not had the financial resources to perform the inventorying, monitoring, and/or research 

necessary to document such effects. 
3 

a. Visibility 

Visitors to national parks and wildernesses list the ability to view unobscured scenic vistas as a 

significant part of a satisfying experience. Unfortunately, visibility impairment has been documented 

in most Class I areas with visibility monitoring. Most visibility impairment is in the form of regional 

haze. The greatest visibility impairment due to regional haze occurs in the eastern United States and in 

southern California, while the least impairment occurs in the Colorado Plateau and Nevada Great 

Basin areas, and in Alaska. Sulfate is primarily responsible for visibility impairment in the eastern 

United States (e.g., Shenandoah National Park in Virginia); in southern California the majority of 

visibility impairment is attributable to nitrates (e.g., San Gorgonio Wilderness); in the Northern Rocky 

Mountains and Pacific Northwest, impairment is primarily due to organics (e.g., Glacier National Park 

in Montana); and in the intermountain West, sulfate, organics and elemental carbon are the main cause 

of impairment (e.g., Grand Canyon National Park in Arizona) (Sisler et al., 1993). 

Visibility impairment on Federal lands can also result from plume intrusion and has been documented 

in Mount Zirkel Wilderness, Moosehorn National Wildlife Refuge, and Grand Canyon National Park. 

 

b. Vegetation 

 

While several components of air pollution (e.g., sulfur dioxide, nitrogen dioxide, and peroxyacyl 

nitrates) can affect vegetation, ozone is generally acknowledged as the air pollutant causing the 

greatest amount of injury and damage to vegetation. The most common visible effects are stipple 

(dark colored lesions on leaves resulting from pigmentation of injured cells), fleck (collapse of a few 

cells in isolated areas of the upper layers of the leaf, resulting in tiny light-colored lesions), mottle 

(degeneration of the chlorophyll in certain areas of the leaf giving the leaf a blotchy appearance), 

necrosis (death of tissue), and in extreme cases, mortality. Aside from visible injury, ozone exposure 

can result in less obvious physiological impairment such as decreased growth or altered carbon 

allocation. 

 

Ozone fumigation experiments have identified a number of plant species that are sensitive to ozone. 

For example, fumigations were conducted in Great Smoky Mountains National Park (Tennessee and 

North Carolina) from 1987 to 1992. On the basis of foliar injury, thirty species were rated as sensitive 

to ozone levels that occurred in the park. The species with foliar injury included black cherry (Prunus 

serotina) and American sycamore (Platanus occidentalis). Additional observations and physiological 

measurements indicated elevated ozone reduced leaf, root, and total dry weights, and increased the 

severity of leaf stipple and premature leaf abscission in these two species (Neufeld and Renfro, 

1993a,b). Field observations have documented foliar injury of these species in other eastern United 

States areas such as Brigantine Wilderness (New Jersey) and Cape Romain Wilderness (South 

Carolina). 

 

Ponderosa pine (Pinus ponderosa) and Jeffrey pine (Pinus jeffreyi) are recognized as good candidates 

for ozone-injury surveys in the western United States, based on their documented sensitivity. For 

example, these species were examined for ozone injury in national parks and national forests in the 

California Sierra Nevada from 1991 to 1995. The sites surveyed included Lassen Volcanic, Yosemite, 

and Sequoia/Kings Canyon National Parks and the Tahoe, Eldorado, Stanislaus, Sierra, and Sequoia 

National Forests. Foliar injury attributable to ozone was found at all areas, and the extent of injury 

generally increased in a southward direction along the Sierra Nevada (Miller et al., 1995). 
4 

c. Soils and Surface Waters 

Acidity in rain, snow, cloudwater, and dry deposition can affect soil fertility and nutrient cycling 

processes in watersheds and can result in acidification of lakes and streams with low buffering 

capacity. Deposition of sulfate to sensitive watersheds results in leaching of base cations, soil 

acidification, and surface-water acidification. In some soils, sulfate adsorption results in "delayed" 

acidification of surface waters. Deposition of excess nitrogen species (nitrate and ammonium) to both 

terrestrial and aquatic systems can result in acidifying streams, lakes, and soils. There is also evidence 

that nitrogen deposition can cause shifts in phytoplankton composition in lakes in which biological 

activity is limited by nitrogen availability, i.e., increased nitrogen deposition can cause phytoplankton 

species that use nitrogen more efficiently to eventually dominate the lake. 

 

Water chemistry surveys and on-going monitoring show that many high elevation lakes on Federal 

lands in the Sierra Nevada, Cascades, and Rocky Mountains are sensitive to acid deposition. In 

general, these lakes are on bedrock that provides them with very little buffering capacity. Some of 

these lakes, for example, Loch Vale in Rocky Mountain National Park (Colorado) experience episodic 

acidification during Spring snowmelt (Baron and Campbell, 1997). 

 

Through funding provided by the Southern Appalachian Mountains Initiative, Herlihy et al. (1996) 

compiled information on surface water sensitivity of streams in nine of the eleven Class I areas in the 

Southern Appalachians. The nine Class I areas were grouped according to geology, physiography, and 

stream chemistry, then the groupings were ranked in terms of effects. Class I areas in the West 

Virginia Plateau (Otter Creek and Dolly Sods Wildernesses) had the highest percentage of acidic 

stream length and lowest pH values. Class I areas in the Northern and Southern Blue Ridge (e.g., 

Shenandoah National Park in Virginia and Joyce Kilmer/Slickrock Wilderness in North Carolina) had 

a lower percentage of acidic stream length, however, streams with low buffering capacity were 

common. The Alabama Plateau Class I area (Sipsey Wilderness) had streams with the highest 

buffering capacity. (Note that the authors based their report on surveys conducted by others and did 

not account for potential differences in methods of data collection.) 

A number of Federal areas contain estuarine and coastal areas that may experience eutrophication as a 

result of excess nitrogen deposition. For example, symptoms of eutrophication, including nutrient 

enrichment and algal blooms, have been observed in Everglades National Park and Chassahowitzka 

Wilderness (Florida). 

3. LEGAL RESPONSIBILITIES 

The specific legal responsibilities that Congress has given FLMs to protect natural, cultural, and scenic 

resources on the public lands from air pollution are identified in Appendix B. Statutes described in 

Appendix B. include agency organic acts, the Wilderness Act, and the Clean Air Act (CAA). 

The fundamental Congressional direction for managing public lands arises out of respective organic 

acts. Each of these laws is essentially a charter from Congress to the Executive Branch providing a 

purpose for parks, wildernesses, and refuges, respectively, and establishing broad management 

objectives for these areas. The Wilderness Act sets aside a subset of these public lands where natural 

processes are allowed to dominate. The agency stewards develop specific management objectives 
5 

building on the organic acts using public involvement, regulations, best available science, and 

additional direction provided by Congress. 

Among this additional Congressional direction is the Clean Air Act (CAA). It further characterizes 

some of the public lands as Class I areas and directs the land managers to take an affirmative 

responsibility to protect these areas from air pollution. The CAA directs that the FLMs identify and 

protect air quality related values, including visibility. This direction is consistent with the underlying 

charters provided by the organic acts and the Wilderness Act. The similarities of management 

objectives, and of the policies and procedures necessary for protecting Class I areas, are at the core of 

the FLAG process. 

In implementing laws, it is essential to understand the “intent of Congress.” In the case of the CAA, 

the FLM gleans additional insight from a passage in Senate Report No. 95-127, 95th Congress, 1st 

Session, 1977 which states, 

“The Federal Land Manager holds a powerful tool. He is required to protect Federal lands 

from deterioration of an established value, even when Class I [increments] are not exceeded. 

... While the general scope of the Federal Government's activities in preventing significant 

deterioration has been carefully limited, the FLM should assume an aggressive role in 

protecting the air quality values of land areas under their jurisdiction. In cases of doubt the 

land manager should err on the side of protecting the air quality-related values for future 

generations.” 

Although the FLMs have an "affirmative responsibility" to protect AQRVs, they have no 

permitting authority under the CAA, and they have no authority under the CAA to establish air 

quality-related rules or standards. The FLM role consists of considering whether emissions from a 

new source may have an adverse impact on AQRVs and providing comments to permitting 

authorities (States or EPA). It is important to emphasize that the FLAG report is only a guidance 

document that explains factors and information the FLMs expect to use when carrying out their 

consultative role. It is separate from Federal regulatory programs. 

The FLAG report describes the steps and process that the FLMs intend to go through in order to 

perform their statutory duties. Consequently, the scope of the FLAG report is to provide a more 

consistent approach for the three FLM agencies to evaluate air pollution effects on their resources, 

and to provide guidance to permitting authorities and permit applicants regarding necessary AQRV 

analyses. Although FLAG strives to be consistent with regulatory programs and initiatives such as 

the Regional Haze Rule and New Source Review Reform, no direct ties exist between FLAG and 

these regulatory requirements. 

4. COMMONALITIES AMONG FEDERAL LAND MANAGERS 

If a new source is proposed near two or more areas managed by different FLMs, the FLMs generally 

try to coordinate in their interactions with the permitting authority and with the applicant. For 

example, two or more FLMs involved in pre-application meetings typically try to minimize the 

workload for the applicant by reaching agreement on the types of analyses the application should 

contain. Beyond coordinating during permit review, FLMs currently base requests and decisions on 

similar principles regarding resource protection and FLM responsibilities. Listed below are the 
6 

common principles in five areas of air resource management. In addition, Appendix C provides the 

FLM’s “GENERAL POLICY FOR MANAGING AIR QUALITY RELATED VALUES IN CLASS 

I AREAS.” 

a. Identifying AQRVs

FLMs agree on the following definition of an AQRV: 

A resource, as identified by the FLM for one or more Federal areas, that may be adversely 

affected by a change in air quality. The resource may include visibility or a specific 

scenic, cultural, physical, biological, ecological, or recreational resource identified by the 

FLM for a particular area.

This definition is compatible with the general definition of AQRV that appears in the Federal Register

(FR 15016, April 10, 1978). That definition includes visibility, flora, fauna, odor, water, soils, 

geologic features, and cultural resources. FLMs have the responsibility to identify specific AQRVs of 

areas they manage. To this end, FLMs further refine AQRVs beyond the above definition to be more 

site-specific (i.e., area specific) by using on-site information. FLMs have developed inventories of 

specific AQRVs for many Class I areas and recognize that, ideally, inventories should be developed 

for all Class I areas. FLMs can be contacted for copies of site-specific AQRV lists. Finally, FLMs 

agree on the need for continued inventory, research, and monitoring to improve their ability to 

determine which AQRVs are most sensitive to air pollution and the sensitivity of these AQRVs. 

b. Determining the Levels of Pollution that Trigger Concern for the Well-Being of AQRVs 

FLMs believe that it should be possible to agree among themselves on the levels of pollution that 

trigger concerns for AQRVs. FLMs recognize the need to assess cumulative impacts and the 

difficulties associated with this process. Difficulties arise when a large number of minor source 

impacts eventually lead to an unacceptable cumulative impact or when a new source applies for a PSD 

permit in an area that has a high background concentration of pollution from existing sources. This 

means that a proposed new source should be evaluated within the context of the total impacts that are 

occurring or that potentially could occur from permitted/existing sources on the AQRVs of the area. 

c. Visibility 

FLMs use EPA-approved models to evaluate visibility impacts. The models use thresholds of 

visibility degradation measured in light extinction to evaluate source impacts to haze (far-field/multisource impacts), and EPA established criteria for coherent plume impacts (near-field impacts). 

Currently all FLMs use Interagency Monitoring of Protected Visual Environments (IMPROVE) 

monitoring data to determine current conditions for visibility in FLM areas. 

d. Biological and Physical Effects 

All FLMs rely on research, monitoring, models, and effects experts to identify and understand 

physical, biological, and chemical changes resulting from air pollution and relating them to changes in 

AQRVs. Further, they focus on sensitive AQRVs (defined as either species or processes) to assess 

this biological/physical/chemical change. 
7 

e. Determining the Level of Pollution Likely to Cause an "Adverse Impact" on AQRVs 

FLMs rely on the best scientific information available in the published literature and best available 

data to make informed decisions regarding levels of pollution likely to cause adverse impacts. FLMs 

re-evaluate, update, and assess this information as appropriate. They consider specific Agency and 

Class I area legislative mandates in their decisions and, in cases of doubt, "err on the side of protecting 

the AQRVs for future generations." (Senate Report No. 95-127, 95th Congress, 1st Session, 1977) 

For air quality dispersion modeling analyses, FLMs follow 40 CFR §52.21(l) (Appendix W of Part 51, 

EPA's Guideline on Air Quality Models, revised 1996) and the recommendations of the Interagency 

Workgroup on Air Quality Modeling (IWAQM). FLMs recommend protocols for modeling analyses 

to permit applicants on a case-by-case basis considering types and amount of emissions, location of 

source, and meteorology. When reviewing modeling and impact analysis results, all FLMs consider 

frequency, magnitude, duration, and location of impacts. 

f. FLM databases 

Air Synthesis (formerly Air Quality Information Management System – AQUIMS) 

Air Synthesis is an information management and decision-support computer system under 

development by NPS and FWS. Air Synthesis is designed to assist FLMs in determining potential 

effects of pollutants on AQRVs. It contains information on air quality and its effects in Class I parks 

and wildernesses as well as natural resource data and annotated bibliographies of current literature on 

ozone and deposition. The system will also contain an interactive expert system module that will 

allow FLMs to assess the current status of freshwaters and determine if these resources are affected 

by deposition of sulfur or nitrogen. 

Natural Resource Information System – Air Module (NRIS-AIR) 

The Air Module is part of the USDA/FS’ Natural Resource Information System that integrates 

various physical, biological, and socioeconomic data within an integrated system of database, mapbased spatial information, and analytical tools. Version 1.0 of NRIS-AIR, released in November 

1998, tracks AQRVs, sensitive receptors, and indicators for each of the USDA/FS Class I areas. 

The water submodule provides data storage, reports, and tools for evaluating locally entered water 

quality and wet deposition data. Future NRIS-AIR versions (currently under development) will 

provide the information structure for visibility, flora, fauna, soil, geologic resources, cultural 

resources, and air quality data, as well as providing a PSD permit tracking system. 
8 

C. FEDERAL LAND MANAGERS' APPROACH TO AQRV PROTECTION 

FLM responsibilities for resource protection on Federal lands are clear and there should be no 

misunderstanding regarding the tools the FLM uses to fulfill these responsibilities. Opportunities to 

influence decisions regarding pollution sources external to the park or wilderness are limited. 

However, FLMs strive to minimize emissions from internal sources and their effects. Approaches for 

minimizing air pollution from external and internal sources are discussed in detail below. 

1. AQRV PROTECTION AND IDENTIFICATION 

Congress assigned the FLMs an affirmative responsibility to protect AQRVs in Federal Class I areas. 

The FLMs interpret this assignment as a responsibility to: 

1. Identify AQRVs in each of the Class I areas. 

2. Establish inventorying and monitoring protocols for AQRVs. 

3. Prioritize AQRV inventorying and monitoring (because of constrained budgets). 

4. Specify a process for evaluating air pollution effects on AQRVs, including the use of 

sensitive indicators. 

5. Specify adverse effects for each AQRV. 

To the extent possible, AQRVs have been identified for each Class I area. Additional AQRVs may be 

identified in the future as more is learned through science about the sensitivity of resources to air 

pollution. Public involvement in this process is necessary and will be accomplished through 

participation in the land management planning process or reply to an announcement in the Federal 

Register. 

While the sensitivity of an AQRV to air pollution may be known, the long term monitoring of its 

health or status may not have been accomplished. The expense of monitoring all AQRVs 

simultaneously is prohibitive. Consequently, FLMs seek opportunities through the permitting process 

and through partnerships to gather more information about condition of AQRVs. 

Because AQRVs themselves are often difficult to measure, surrogates are used as indicators, or 

sensitive indicators, of the health or status of the AQRV. Designing a working process for Class I area 

management and AQRV protection is outlined ahead in this document. 

Finally, an adverse impact is determined for each AQRV. An adverse impact from air pollution 

results in a diminishment of the Class I area’s national significance, that is, the reason the Class I area 

was created. Adverse impacts can also be an impairment of the structure or functioning of the 

ecosystem as well as an impairment of the quality of the visitor experience. The FLMs make an 

adverse impact determination on a case-by-case basis, based on technical and other information. 

2. NEW SOURCE REVIEW 

Section 165 of the CAA spells out the roles and responsibilities for FLMs in New Source Review, 

including the Prevention of Significant Deterioration (PSD) permitting program. Other laws, such as 

the respective agency organic acts and the Wilderness Act, provide the fundamental underpinning of 

land management direction to land managers. The following discussion merges this complex 
9 

labyrinth of legal responsibilities as it relates to air resource management. A pending regulation 

revision from EPA which contains many of the items in this section addressing NSR may add more 

specificity to the Class I area protection process from the perspective of the CAA. 

a. Roles and Responsibilities of FLMs 

The FLM. The federal official directly responsible for the national parks, national wildlife refuges, 

and national forests (e.g., park superintendents, refuge managers, and forest supervisors, respectively) 

derive their responsibility from the respective agency organic acts. Furthermore, these officials, and 

the FLM for the respective agencies, have an affirmative responsibility under Section 165 of the CAA 

to protect and enhance the AQRVs of Class I areas from the adverse effects of air pollution. The FLM 

for the USDA/FS is the Regional Forester or the Forest Supervisor depending on the specific location. 

The FLM for the NPS and FWS is the Department of the Interior’s Assistant Secretary for Fish and 

Wildlife and Parks. 

Visibility Protection Program for New and Modified Sources. The FLMs have visibility 

protection responsibility under 40 CFR §51.307 (New source review), which spells out the 

requirements for State Implementation Plan (SIP) visibility protection programs, as well as 40 CFR 

§52.27 (Protection of visibility from sources in attainment areas) and 40 CFR §52.28 (Protection of 

visibility from sources in non-attainment areas). These three provisions, taken together along with 

the SIP-approved rules, establish the visibility protection program for new and modified sources 

throughout the country. 

Notification. Section 165 (42 USC, 7475) of the CAA requires the EPA, or the State/local permitting 

authority, to notify the FLM if emissions from a proposed project may impact a Class I area. The 

permitting authority should forward PSD applications to the FLM for review and analysis as soon as 

possible after receipt, giving the FLM an opportunity to review the application concurrently with the 

permitting authority. 

Generally, the permitting authority should notify the FLM of all new or modified major facilities 

proposing to locate within 100 km (62 miles) of a Class I area. In addition, the permitting authority 

should notify the FLM of "very large sources" with the potential to affect Class I areas proposing to 

locate at distances greater than 100 km. (Reference March 19, 1979, memorandum from EPA 

Assistant Administrator for Air, Noise, and Radiation to Regional Administrators, Regions I - X). 

Given the multitude of possible size/distance combinations, the FLMs can not precisely define in 

advance what constitutes a "very large source" located more than 100 km away that may impact a 

particular Class I area. Therefore, the FLM and permitting authority should work together to 

determine which PSD applications the FLM is to be made aware of in excess of 100 km. The FLM 

and permitting authority should make this determination on a case-by-case basis, considering such 

factors as: 

• Current conditions of sensitive AQRVs; 

• Magnitude of emissions; 

• Distance from the Class I area; 

• Potential for source growth in an area/region; 

• Existing/prevailing meteorological conditions; 

• Cumulative effects of several sources to AQRVs. 
10 

Additionally, such dialogue facilitates coordination between permitting authorities and the FLMs. 

The significance of the impact to AQRVs is more important than the distance of the source. Not all 

PSD permit applications that the FLM is notified of will be analyzed in-depth by the FLM. FLM 

notification of a PSD permit application for a project located greater than 100 km does not mean 

that that application will be reviewed by the FLM in detail. Notification of PSD permit 

applications in excess of 100 km by the permitting authority allows the FLM to gauge the level of 

potential cumulative effects. As indicated above, the FLM decides which PSD permit applications 

to review on a case-by-case basis depending on the potential impacts to AQRVs. 

Pre-Application Meetings. To expedite the PSD permit review process, the FLM encourages preapplication meetings with permitting authorities and permit applicants to discuss air quality concerns 

for a specific Class I area in question. Given preliminary information, such as the source's location 

and the types and quantity of projected air emissions, the FLM can discuss specific AQRVs for an area 

and advise the applicant of the analyses needed to assess potential impacts on these resources. 

Completeness Determination. To further minimize delays, the FLMs encourage the permitting 

authority to use comments provided by the FLM concerning the completeness of the application, and 

to not deem the application complete until the applicant performs all necessary air quality impact 

analyses, including all relevant AQRV impact information. The permitting authority should then 

notify the FLM when they deem the application to be complete. 

Visibility Protection Procedures. Additional procedural requirements apply when a proposed source 

has the potential to impair visibility in a Class I area (40 CFR §52.27(d)(1998)). Specifically, the 

permitting authority must, upon receiving a permit application for a source that may affect visibility in 

any Class I area, notify the FLM in writing. Such notification should include a copy of all information 

relevant to the permit application, including the proposed source's anticipated impacts on visibility in a 

Class I area. The permitting authority should notify the FLM within 30 days of receipt and at least 60 

days prior to the close of the comment period. 

If the FLM notifies the permitting authority that the proposed source may adversely impact visibility 

in a Class I area, or may adversely impact visibility in a previously identified integral (scenic) vista, 

then the permitting authority is to work with the FLM to address their concerns. If the permitting 

authority agrees with the FLM's finding that visibility in a Class I area may be adversely affected, the 

permit may not be issued. Even though the permitting authority may agree with the FLM's adverse 

impact finding regarding integral vistas, the permitting authority may still issue a permit if the 

emissions from the source are consistent with reasonable progress toward the national goal of 

preventing or remedying visibility impairment. In making this decision, the permitting authority may 

take into account the costs of compliance, the time needed for compliance, the energy and non-air 

quality environmental impacts of compliance, and the useful life of the source. 

The FLM will make a preliminary determination regarding possible adverse visibility impacts within a 

prescribed time of receipt of all relevant information. 

b. Elements of Permit Review 

The FLM review of a PSD application for a proposed project that may impact a Class I area generally 

consists of three main analyses: 
11 

1. Air quality impact analysis to ensure that predicted pollutant levels in Class I areas do 

not exceed National Ambient Air Quality Standards (NAAQS) and PSD increments, 

and to provide sufficient information for the FLM to conduct an AQRV impact 

analysis. Ensuring that permit applicants meet these requirements is the direct 

responsibility of the permitting authority (see discussion below); 

2. AQRV impact analysis to ensure that the Class I area resources (i.e., visibility, flora, 

fauna, etc.) are not adversely affected by the proposed emissions. The AQRV impact 

analysis includes interpreting the significance of the results from the applicant’s air 

quality impact analysis and is the responsibility of the FLM (see discussion below); 

and 

3. Best Available Control Technology (BACT) analysis to help ensure that the source 

installs the best control technology to minimize emission increases from the proposed 

project (See Appendix D for a summary of this analysis). The final BACT 

determination is a direct responsibility of the permitting authority. 

Air Quality Impact Analysis. The permit applicant must perform an air quality impact analysis for 

each pollutant subject to PSD review. This analysis should show the contribution of the proposed 

emissions to increment consumption and to the existing ambient pollution levels in a Class I park or 

wilderness area. The applicant should perform a cumulative increment analysis for each pollutant and 

averaging time for which the proposed source will have a significant impact. Because proposed sources 

are not yet operating, the air quality analysis must rely on mathematical dispersion models to estimate 

the air quality impact of the proposed emissions. The FLMs provide the applicants with guidance on 

where to place model receptors within the Class I area. The applicant is responsible to provide 

sufficient information for the FLM to make a decision about the acceptability of potential AQRV 

impacts as a consequence of the new source. 

The applicant should perform the air quality impact analysis using approved models and procedures 

as specified in 40 CFR §52.21(l) and 40 CFR §51.166(l) (Appendix W of Part 51, EPA's Guideline 

on Air Quality Models, revised 1996 and in revision again as of the date of this writing, December 

2000). The applicant should explicitly state all assumptions for the analysis, and furnish sufficient 

information on modeling input so that the FLM can validate and duplicate the model results. FLMs 

encourage the permit applicant to submit a modeling protocol for review before performing the 

Class I modeling analyses. This protocol should include the proposed air quality analysis 

methodology and model input (i.e., emissions, stack data, meteorological data, etc.), and the 

proposed location of the receptors in the FLM area. 

AQRV Impact Analysis. According to the CAA’s legislative history and current EPA regulations 

and guidance, the air quality impact analysis that provides sufficient information to enable the FLM 

to conduct the AQRV impact analysis is one part of a permit application just as are the BACT 

analysis and the air quality impact analysis relative to the increments and NAAQS. The applicant 

bears the entire cost of preparing the permit application including the complete air quality impact 

analysis. 

The FLM then uses the results from the applicant's air quality impact analysis and other 

information to conduct the AQRV impact analysis and make an informed decision about whether 

or not AQRVs will be adversely affected. If the FLM concludes that AQRVs are or will be 
12 

adversely affected, the FLM must so demonstrate to the permitting authority. The following 

sections of this document give guidance to applicants on how to conduct an air quality impact 

analysis and how the FLM uses this information to make an AQRV impact decision. 

Cumulative Impact Analysis. The applicant’s air quality impact analysis should include both the 

permit applicant’s contribution to the AQRV impacts, as well as the cumulative source impacts on 

AQRVs. A cumulative air quality analysis in which the proposed source and any recently 

permitted (but not yet operating) sources in the area are modeled is an important part of any AQRV 

impact analysis. This cumulative modeled impact is then added to measured ambient levels (to the 

extent that such monitoring data are available) so that the FLM can assess the total effect of the 

anticipated ambient concentrations on AQRVs. If no representative monitoring data are available, 

the applicant should estimate the total pollutant concentrations by modeling emissions from all 

contributing sources in the area. 

Information Provided by the FLM to the Applicant. To assist the permit applicant in 

performing air quality impact analyses, the FLMs will provide all available information about 

AQRVs for a particular Class I area that may be adversely affected by emissions from the proposed 

source. FLMs will recommend available methods the applicant should use to analyze the potential 

effects to the receptor(s) located in the Class I area. In addition to identifying AQRVs, FLMs will, 

to the extent possible: 

(1) identify inventories, surveys, monitoring data, scientific studies, or other published 

reports that are the basis for identification of AQRVs; 

(2) identify specific receptors known to be most sensitive to air pollution and the pollutant 

or pollutants that individually or in combination can cause or contribute to an adverse 

effect on each receptor; 

(3) Identify the critical pollutant concentrations above which adverse effects are known or 

suspected to occur; 

(4) Recommend methods the applicant should use for predicting ambient pollutant 

concentrations and other related impacts (e.g., deposition, visibility) which may cause 

or contribute to an adverse effect on each receptor; and 

(5) Suggest screening level values or criteria that would be used to assess whether a 

proposed emissions increase would have a de minimis impact on AQRVs. 

It is important to highlight the distinction between the air quality impact analyses that the applicant 

performs and the AQRV impact analyses that FLMs perform. Whereas the permit applicant calculates 

changes in pollutant concentrations, deposition rates, or visibility extinction, the FLM assesses the 

extent to which these impacts affect sensitive visual, aquatic, or terrestrial resources. Given the FLM’s 

statutory responsibilities and expertise, the FLM must have responsibility to consider whether the 

amount of pollution dispersed into the air or deposited on the ground (or in water) would have an 

adverse impact on any AQRV, and if so, to demonstrate that claim to the permitting authority. In 

making an adverse impact finding, FLMs consider such factors as magnitude, frequency, duration, 

location, and timing of impacts, as well as current and projected conditions of AQRVs based on 

cumulative impacts. 
13 

c. FLM Permit Review Process 

The FLM's current permit review process for any application that may impact a FLM area is described 

below. 

 

1. Pre-application. If possible, participate in any pre-application meeting to learn specifics of the 

proposed project (size, emissions, location, etc.) and to provide information regarding 

recommended Class I analyses. 

2. Completeness Determination. Upon receipt, the FLM will review the application and 

provide comments to the permitting authority regarding the completeness of the application 

and the need for additional information regarding the BACT, Air Quality Impacts, and AQRV 

Impacts analyses. The FLM will coordinate with the permitting authority and the permit 

applicant to ensure that all the necessary information to enable the FLM to make an impact 

determination is included. 

3. Public Comment Period. After review of all relevant information, the FLM will provide 

pertinent comments to the permitting authority, before or during the official public comment 

period, and/or at scheduled public hearings. 

4. No Class I Increment Violated and No Adverse Impacts. If no Class I increment is 

violated and no adverse impacts to AQRVs are expected, the FLM will inform the permitting 

authority of this determination and no further FLM action is necessary. The FLM may still 

provide BACT comments. 

5. No Class I Increment Violated but AQRV Impact Uncertainty. If no Class I increment is 

violated but uncertainty exists regarding potential adverse impacts to AQRVs, the FLM may 

request that the permitting authority include a permit condition that requires the permittee to 

conduct relevant post-construction AQRV or air quality monitoring. The FLM may also 

request certain control technologies or methods to reduce impacts. 

6. Class I Increment Violated, but No Adverse AQRV Impacts. If the Class I increment is 

violated, but no adverse AQRV impacts are anticipated, the applicant requests the FLM to 

"certify" no adverse impact under Section 165(d)(2)C)(iii) of the Clean Air Act [42 USC 

7475(d)(2)(C)(iii)(1998)]. If the FLM concurs, (s)he makes a preliminary determination that 

no adverse impacts will occur. 

a. The FLM will inform the applicant, the State/local permitting authority, and EPA of 

the preliminary no adverse impact determination. 

 

b. The FLM will notify the public of its preliminary no adverse impact determination 

either through the permitting authority's notice procedures, or through separate notice 

in the Federal Register. Such notice should include a statement as to the availability of 

supporting documentation for inspection and copying, and an announcement of at least a 30-

day public comment period on issues directly relevant to the determination in question. 

c. The FLM will review and prepare response to public comments. 
14 

d. The FLM will make a final determination regarding no adverse impacts, with a clear 

and concise statement of reasons supporting that determination. 

e. The FLM will inform the permit applicant, the permitting authority, and EPA of its 

final determination and if the final determination is "no adverse impact," the FLM shall 

so "certify" in a letter to the affected parties. 

f. Simultaneous with step e, the FLM will publish a final determination in the "Notice" 

section of the Federal Register, including a clear and concise statement of reasons 

supporting that determination, statement as to availability of supporting documentation 

for inspection and copying, and statement as to immediate effective date (date signed) 

of final determination. 

g. The FLM will contact the permitting authority and request a revision to the State 

Implementation Plan (SIP) to eliminate the Class I increment violations. 

7. Adverse Impact Determination. Regardless of increment status, the FLM may make a 

preliminary determination that the proposed project will cause, or contribute to, an adverse 

impact on AQRVs. Before officially declaring an adverse impact, the FLM will inform the 

proposed new source and the permitting authority that an adverse impact determination is 

imminent and suggest that the permit be modified. If the permit is modified to satisfy the 

concerns of the FLM, then an adverse determination is avoided. 

a. The FLM will inform the applicant, the permitting authority, and EPA of a preliminary 

adverse impact determination. 

b. The FLM will notify the public of the preliminary adverse impact determination either 

through the permitting authority's notice procedures, or through separate notice in the 

Federal Register. Such notice should include a statement as to the availability of 

supporting documentation for inspection and copying, and an announcement of at least 

a 30-day public comment period on issues directly relevant to the determination in 

question. 

c. The FLM will review and prepare response to public comments. 

d. The FLM will make a final determination regarding adverse impacts, with a clear and 

concise statement of reasons supporting that determination. 

e. The FLM will inform the permit applicant, the permitting authority, and EPA of its 

final determination. 

f. Simultaneous with step e, the FLM will publish a final determination in the "Notice" 

section of the Federal Register, including a clear and concise statement of reasons 

supporting that determination, statement as to availability of supporting documentation 

for inspection and copying, and statement as to immediate effective date (date signed) 

of final determination. 
15 

g. If the FLM makes a final determination that a source will have an adverse impact, the 

FLM will oppose the permit. However, the permit applicant may propose to mitigate 

any adverse impacts (via reducing emissions, obtaining emission offsets, etc.). If the 

applicant adequately mitigates the adverse impacts to the satisfaction of the FLM, the 

FLM will withdraw his objection to the permit. If the adverse impacts are not 

adequately mitigated and the permitting authority nevertheless issues the permit, the 

FLM may appeal the permit. 

Note: If the permitting authority's SIP makes execution of the above listed steps impossible (e.g., 

inadequate time allotments for the FLM's determination or lack of timely FLM notice ) the procedures 

shall be adjusted as appropriate. In addition, the above procedures (6 and 7) could also be modified to 

accommodate those situations when the FLM chooses to certify that existing impacts are adverse, 

absent a proposed new source. Such an action would alert potential permit applicants that adverse 

impacts exist and any new source would need to mitigate its potential impacts. Although each FLM 

may implement the above procedures somewhat differently, the FLAG goal is to reduce the 

differences in implementing the above steps. 

Furthermore, FLMs intend to coordinate on air permit modeling requirements for new or modified 

sources that are geographically near more than one FLM area. For example, a proposed source in 

eastern Tennessee that lies equidistant from NPS-administered Great Smoky Mountains National Park 

and the FS-administered Joyce Kilmer/Slickrock Wilderness would receive coordinated guidance on 

modeling requirements from the FLMs. The FLMs may or may not have common AQRVs at different 

Class I areas, making coordination beneficial. The FLMs may also coordinate on potential permit 

conditions and mitigation strategies. 

d. Criteria for Decision Making (Adverse Impact Considerations) 

As previously mentioned, the legislative history of the CAA provides direction to the FLM on how to 

comply with the affirmative responsibility to protect AQRVs in Class I areas, and in cases of doubt, 

the land manager should err on the side of protecting air quality-related values for future generations. 

The FLMs define adverse impact on AQRVs as: 

An unacceptable effect, as identified by an FLM, that results from current, or would result 

from predicted, deterioration of air quality in a Federal Class I or Class II area. A 

determination of unacceptable effect shall be made on a case-by-case basis for each area taking 

into account existing air quality conditions. It should be based on a demonstration that the 

current or predicted deterioration of air quality will cause or contribute to a diminishment of 

the area's national significance, impairment of the structure and functioning of the area's 

ecosystem, or impairment of the quality of the visitor experience in the area.

Also, the Federal visibility protection regulations (40 CFR §51.300, et seq., §52.27) define adverse 

impact on visibility as: 

[V]isibility impairment which interferes with the management, protection, preservation or 

enjoyment of the visitor's visual experience of the Federal class I area. This determination must 

be made on a case-by-case basis taking into account the geographic extent, intensity, duration, 

frequency, and time of visibility impairment, and how these factors correlate with: (1) times of 
16 

visitor use of the Federal class I area, and (2) the frequency and timing of natural conditions 

that reduce visibility. (Id. §51.301(a)) 

FLMs typically address adverse impacts on a case-by-case basis in response to PSD permit 

applications. When an adverse impact is predicted, FLMs recommend that permits either be modified 

to protect AQRVs or be denied. FLMs can also address adverse conditions outside of the PSD 

process. To do so, they: certify visibility impairment; participate in regional assessments; informally 

collaborate with States and EPA; review lease permits, SIP revisions, National Environmental Policy 

Act (NEPA) analyses, Park/Refuge/Forest management plans, CERCLA (Comprehensive 

Environmental Response, Compensation, and Liability Act) reviews, and other documents. 

In some States, FLMs use screening procedures or thresholds that indicate when the condition of an 

AQRV is acceptable or unacceptable. The pollutant concentration or loading rate that will adversely 

impact an AQRV can vary among Class I areas, and depends on current conditions. After a threshold 

is reached, an increase in pollutant concentrations is likely to be unacceptable. A concern threshold 

can be an adverse impact threshold or other quantifiable level in resource condition or pollutant 

exposure identified by the FLM. 

e. Air Pollution Permit Conditions that Benefit Class I Areas 

The FLM does not determine what permit conditions will be required or administer permit conditions; 

that is the responsibility of the permitting authority. However, the FLMs may request permit 

conditions or agree to withdraw objections to permit issuance if requested conditions are included. 

The FLMs view the inclusion of certain PSD permit conditions by the permitting authority as a means 

to help protect or enhance the condition of AQRVs when: 

1. Air pollution source(s) may cause impacts that exceed protection thresholds for 

AQRVs; 

2. Terrestrial resources, aquatic resources, and/or visibility are currently adversely 

impacted by air pollution and proposed emissions will exacerbate these adverse 

conditions; 

3. FLM policies require improvement or restoration of AQRVs in parks and 

wildernesses; and 

4. There is uncertainty on the extent and magnitude of air pollution effects on AQRVs. 

Permit conditions may require emission offsets, AQRV and/or air quality monitoring, inventories, reopeners, LAER (or other improved control technologies), or other measures to protect, enhance, or 

restore resources and values of parks and wildernesses. Permit conditions may: 

1. Result in net air quality benefits at a protected area or within a region; 

2. Contribute to a reduction of air pollution within a region; 

3. Promote ecosystem inventories and/or monitoring to evaluate physical and biological 

resource damage caused by air pollution emissions; and 

4. Promote ecosystem restoration or improve the condition of resources damaged by air 

pollution emissions. 
17 

The basis of an air permit condition may be identified in the public notice for the draft permit. To be 

effective, permit conditions must be federally enforceable and guaranteed. Air permit provisions may 

be temporary or permanent depending on the nature of the permit requirements. Procedures to 

implement an air permit condition must be acceptable to the FLM (e.g., an agreement between parties 

[memorandum of understanding, interagency agreement] is an option to accomplish inventory, 

monitoring, or other requirements). 

f. Reducing Pollution in Nonattainment Areas (Nonattainment Permit Process) 

The PSD program does not apply with respect to a particular pollutant when the source locates in 

an area designated non-attainment for that pollutant. Instead, pollution sources are regulated by 

Non-attainment Area New Source Review (NNSR). NNSR includes air quality planning and 

regulation of stationary sources. Air quality planning addresses issues such as lowest achievable 

emission rate (LAER), offsets, reasonably available control technology (RACT), and mobile and 

stationary source control strategies. New major stationary sources and major modifications of 

sources in designated non-attainment areas must satisfy NNSR before construction begins. For 

visibility protection, SIPs must include either EPA-approve provisions to comply with 40 CFR 

§51.307 for the non-attainment pollutant, otherwise, the federally promulgated visibility provisions 

at 40 CFR §52.28 would apply to all sources located in non-attainment areas. Therefore, FLMs can 

provide suggestions to the permitting authority regarding these conditions during the permitting 

and planning processes. 

SIPs provide a mechanism to address AQRV impacts for when the source or the Class I area is located 

in a non-attainment area. Land managers should recommend that States adopt policies, rules, or 

regulations in their SIPs requiring a demonstration that offsets will result in a net air quality benefit 

within any Class I area likely to be impacted by emissions from the source to be permitted. FLMs 

may also request emissions reductions greater than 1:1, perhaps offset rates of 1.5 or 2.0 to 1, or 

higher, depending on the impacts to be offset. Such recommendations can be developed jointly in a 

meeting with the regulatory authority or in a letter from the FLM. 

Mitigation measures recommended by FLMs may include stringent control technologies to 

minimize the increase in emissions and the impact on AQRVs. Monitoring can determine whether 

predicted resource conditions are observed. Offsets ensure that net emissions reductions from all 

sources will occur within a geographic area and their resulting air quality impacts at the Class I area 

will be mitigated. 

3. OTHER AIR QUALITY REVIEW CONSIDERATIONS 

At all Class I areas where visibility has been monitored, visibility conditions have been found to be 

impaired (by human-caused pollution). The impairment comes primarily from older sources, not new 

sources. From a regional perspective, new or modified sources (using new/cleaner technologies) 

contribute far less to impaired AQRV conditions than old sources. New programs, such as EPA’s 

NAAQS for fine particulate matter and 8-hour ozone levels have been legally challenged (as of 

December 2000) so their effectiveness in reducing overall regional pollutant levels from older sources 

is uncertain at this time. EPA has implemented a call for reducing NOx emissions from older sources 

in the eastern U.S. to meet existing ozone standards, however, this action is being appealed to the U.S. 

Supreme Court. In addition to national ambient standards, most States are just now beginning the 

planning process to implement EPA’s Regional Haze Regulations. If all of these requirements are 
18 

implemented, then progress toward remedying impaired AQRVs is likely. However, given the 

sensitivity of some AQRVs to low levels of pollution, programs focused on reaching national goals, 

such as the NAAQS or visibility, may not fully remedy impacts on AQRVs in all locations. It is for 

this reason that the FLM should pursue all other reasonable strategies to protect AQRVs. The 

following sections discuss FLM issues that go beyond NSR. 

a. Remedying Existing Adverse Impacts 

The existence of adverse impacts is unacceptable to FLMs and contrary to the mandates of their 

specific agencies. Consequently, FLMs may request or participate in regional assessments to protect 

AQRVs, as appropriate. Regional assessments often use a multi-faceted approach to remedy 

impairment. For example, categories addressed by the Grand Canyon Visibility Transport 

Commission (GCVTC) include air pollution prevention; clean air corridors; stationary sources; 

sources in and near Class I areas; mobile sources; road dust; fire; and future regional coordination. 

Clean Air Act requirements for remedying existing visibility impairment provide a mechanism for 

addressing impacts from specific sources or groups of sources. Negotiations at the Centralia Power 

Plant in the state of Washington provide an example of how to build partnerships and work 

collaboratively to obtain retrofit controls or more stringent control technologies for sources that affect 

a FLM area. Through a collaborative decisionmaking process, owners of the Centralia plant agreed to 

reduce sulfur dioxide emissions at the plant by 90%. In another case, the USDA/FS asked the state of 

Colorado to remedy existing impairment at Mt. Zirkel Wilderness. Following USDA/FS testimony 

about the Mt. Zirkel Wilderness, terms of a court-ordered consent decree that specified controls for the 

Hayden Power Plant were included in Colorado’s long-term visibility strategy. 

FLMs may also coordinate with others to ensure that emission reductions in nonattainment areas will 

improve air quality in FLM areas. Recommendations on urban planning were developed with FLM 

involvement to address nonattainment areas in California. Data documenting ozone effects on 

vegetation were provided to the planning authority. 

b. Requesting SIP Revisions to Address AQRV Adverse Impacts 

A SIP is the key vehicle a state uses to develop the pollution control programs that will be used to 

achieve and maintain the NAAQS as well as prevent significant deterioration of air quality. It is 

important for FLMs to be involved in SIP development, as participation provides an opportunity to 

influence planning of pollution control programs that can benefit air quality in FLM areas. Once a SIP 

is fully approved by EPA, it is legally enforceable under both State and Federal law. FLMs can use 

the SIP process to address existing impacts that are unacceptable by requesting a SIP revision. This 

approach is particularly useful for addressing impacts on AQRVs other than visibility, since the Clean 

Air Act does not provide specific requirements for other AQRVs. In an October 16, 1996, letter from 

the Deputy Assistant Administrator of the EPA to the Assistant Secretary of the Department of the 

Interior (DOI), the EPA acknowledged that the CAA provides authority to address adverse impacts on 

AQRVs in Class I areas from both new and existing sources. EPA committed to initiate rulemaking 

that will set forth the affirmative obligation for States to protect AQRVs as part of their CAA 

responsibility to prevent significant deterioration of air quality. EPA states this approach would require 

the protection of AQRVs as part of SIPs. 
19 

In an October 17, 1996, response, DOI offered to assist EPA in developing this adverse impact SIP 

rulemaking. In addition, DOI urged EPA "to require State Implementation Plans to prevent significant 

deterioration of air quality by adopting mitigation measures to address adverse impacts on AQRVs in 

Class I areas." These SIP revisions could be used to address multiple sources and regional pollution 

that adversely affect AQRVs in all Class I areas. DOI sent a follow-up letter to EPA in July 2000 

reiterating the need for an AQRV “restoration and protection” rulemaking. EPA solicited public input 

regarding an AQRV rule, as well as a request from Northeastern states for more stringent secondary 

NAAQS. EPA will consider comments received and then decide on a course of action. 

South Coast and San Diego, California, SIP revisions included FLM recommendations to reduce the 

impact of minor sources on AQRVs. South Coast recommendations addressed visibility while the San 

Diego recommendations addressed all AQRVs. EPA's NOX SIP Call in the east is another example of 

obtaining emission reductions through the SIP revision process. The NOX SIP Call is directed at 20 

eastern States and the District of Columbia to address NOX emissions from existing large sources. 

Once this action is implemented, significant reductions in ozone formation and nitrogen deposition are 

anticipated. 

c. Periodic Increment Consumption Review 

As mentioned above, EPA has indicated its intention to the FLMs to establish a SIP revision 

requirement to address existing adverse impacts on AQRVs. The FLMs strongly support EPA 

exercising its authority in this way. In the interim, however, there are existing SIP revision 

requirements that are not being fully utilized. EPA's current regulations require States to conduct a 

periodic review of the adequacy of their PSD plan and program. [40 CFR §51.166(a)(4)] This would 

include an assessment of increment consumption in Class I and Class II areas. Few States have ever 

conducted a comprehensive, cumulative increment consumption analysis for one or more Class I 

areas. In addition, many PSD sources have not exceeded the significant impact levels for increment 

consumption; thus, few PSD permit applicants have had to perform a cumulative increment 

consumption analysis for Class I areas. Such a periodic increment consumption review would be 

beneficial given that the burden of proof for AQRV adverse impact determinations shifts from the 

FLM to the applicant when the increment has been consumed. 

In its 1990 report Air Pollution: Protecting Parks and Wilderness From Nearby Pollution Sources the 

U.S. General Accounting Office (GAO) found that only 1 percent of the sources within 100 kilometers 

of five Class I areas it investigated were required to have permits under the PSD program, with 99 

percent of the sources being minor or grandfathered sources. It also found that “non-PSD sources 

contribute from 53 to 90 percent of five of the six criteria pollutants emitted within a 100-kilometer 

radius of each of the 5 Class I areas.” As part of its investigation, GAO noted that “a significant 

portion of total emissions of volatile organic compounds generally comes from small sources...and 

suggested that as part of the overall control strategy, States may want to consider lowering thresholds 

for regulating new sources to 25 tons of volatile organic compounds a year.” According to the 

investigation, 55 percent of anthropogenic VOC emissions come from new sources or modifications 

totaling 5 tons per year or less. In a review of PSD permit applications near Mesa Verde National Park 

(a Class I area in Colorado), a cumulative modeling analysis of increment-consuming sources found 

that approximately 80 percent of the NO2 Class I increment at the park had been consumed, but much 

of it by minor sources. 
20 

The FLMs have encouraged EPA to provide clearer direction on how often these periodic reviews 

must occur as the lack of a prescribed time-frame for conducting such analyses has clearly led to 

noncompliance with this requirement over the past twenty years by States. The FLMs believe EPA 

should revise 40 CFR §51.166 to require that the periodic reviews be conducted no less frequently 

than every five years. 

4. MANAGING EMISSIONS GENERATED IN AND NEAR FLM AREAS 

Specific strategies need to be developed and implemented for reducing and preventing pollution from 

the many diverse sources and activities in communities surrounding FLM areas, including “gateway” 

communities. Accountability mechanisms are needed to ensure that appropriate actions are taken, 

reported and incorporated into SIPs, visibility protection plans, and Federal land management plans. 

Various forums (e.g., the Western Regional Air Partnership, and the Southern Appalachian Mountains 

Initiative) are addressing some of the emissions sources of concern and developing appropriate 

regional strategies. In addition, EPA has formed other “regional planning organizations” for 

implementing its regional haze rule. FLMs should participate in these forums, consistent with Federal 

law (e.g., Federal Advisory Committee Act), to the maximum extent possible and should coordinate 

their activities within those forums to ensure that comprehensive strategies are developed and 

implemented to address all the key emissions sources near FLM areas. 

 

A systematic assessment of emission sources in and near FLM areas would be extremely helpful for 

formulating strategies aimed at mitigating or eliminating adverse impacts on area resources. Without 

this assessment it is not possible to accurately quantify the extent to which these emissions contribute 

to the overall problem. Nevertheless, FLMs can, and should, take steps to minimize emissions 

generated on FLM lands even without an accurate inventory of emissions sources. 

a. Prescribed Fire 

Prescribed fire is a land management tool used for multiple landscape objectives. Prescribed fire 

allows the FLM to mimic natural fire return intervals under controlled conditions where smoke 

management can minimize air quality impacts. The alternative is wildfires, which can be very difficult 

to control and may cause much more severe air quality impacts. A modeling assessment suggests that 

using prescribed fire to minimize wildfires can result in a net reduction in fine particle (PM2.5) 

emissions in the long term. In the Pacific Northwest wildfire emissions were found to be greater than 

prescribed fire emissions in the same airshed (Ottmar, 1996). 

Since the turn of the century, wildfire has been aggressively suppressed on most of the nation's public 

lands to protect public safety, property, and to prevent what was thought to be the destruction of our 

natural and cultural resources. Fire-exclusion practices have resulted in forests, shrub lands, and 

grasslands plagued with a variety of problems, including overcrowding, resulting from the 

encroachment of species normally suppressed by fire; vulnerability of trees to insects and disease; and 

inadequate reproduction of certain species. In addition, heavy accumulation of fuels (such as dead 

vegetation on the forest floor) can cause fires to be catastrophic, which threatens firefighter and public 

safety, impairs forest and ecosystem health, destroys property and natural and cultural resources, and 

degrades air quality. The intense or extended periods of smoke associated with wildfires can also 

cause serious health effects and significantly decrease visibility. 
21 

FLMs recognize prescribed fire as a valuable tool; they also recognize that emissions from prescribed 

fire can be a significant source of air pollution. Smoke particles are also in the size range (< 2.5 μm) 

that they play a significant role in visibility impairment. Particulate matter is the main pollutant of 

concern from smoke because it can cause serious health problems, especially for people with 

respiratory illness. 

The FLMs are committed to minimizing the impacts from smoke by following sound smoke 

management practices, and if practical, using alternative methods to achieve land management 

objectives. Each prescribed burn site will have unique characteristics, but in general, smoke impacts 

can be greatly minimized by burning during weather conditions that provide optimal humidity levels 

and dispersion conditions for the type of materials being burned, in addition to limiting the amount of 

materials and acreage burned at one time. 

Generally, fire inside wilderness is considered natural–there is a need whenever possible to allow these 

fires to burn out naturally when the fires do not threaten private property or air quality conditions do 

not threaten human health. Visibility impairments caused by naturally ignited fires in wilderness 

should similarly be classified as natural. Unlike stationary source emissions, which are continuous, fire 

emissions are spatially and temporally sporadic.

EPA has worked in partnership with land management agencies in the U.S. Departments of 

Agriculture, Defense, and the Interior; State Foresters; State air regulators; Tribes; and others to obtain 

recommendations and develop a national policy that addresses how best to improve the quality of 

wildland ecosystems (including forests and grasslands) and reduce threats of catastrophic wildfires 

through the increased use of managed fire, while achieving national clean air goals (U.S. EPA, 1998). 

EPA’s wildland fire policy describes criteria for wildland managers (federal, state, tribal, and private), 

and state and tribal air pollution agencies, to use in planning for and implementing prescribed fires, 

and recommends a variety of smoke management techniques that land managers can use to help 

reduce smoke impacts from prescribed fires. The policy is available at EPA’s website: 

http://www.epa.gov/ttn/faca/fa08.html. 

b. Strategies to Minimize Emissions from Sources In and Near FLM Areas 

Aside from prescribed fire, other activities that generate air pollution in FLM areas include road 

building, operation of generators, oil and gas development, etc. Developing strategies for addressing 

natural resource impacts in or near an FLM area should not only take into consideration the type of 

activities generating the emissions and their amount, but also the existing condition of the resources of 

that area. More stringent measures should be required for sources in and near FLM areas that are 

already experiencing adverse effects from air pollution. 

Examples of potential air pollution prevention practices that FLM agencies may encourage or develop 

and use are categorized under the following three strategies: 

Pollution Prevention Strategies

 Review land management plans for affected FLM areas to assess whether they include strategies to 

limit and reduce air pollution emissions and incorporate protective measures into planning and 

decision documents. 

 Place priority on pollution prevention. 
22 

 Encourage zero and near-zero emitting technologies. 

 Promote energy conservation and the use of renewable energy sources. 

 Promote use of clean fuels. 

Mobile Source Strategies

 Promote the adoption of Low Emission Vehicle standards or the conversion of Federal fleets to 

alternative fuels. 

 Improve control of evaporative emissions. 

 Adopt and enforce more stringent emission standards for the tour bus industry and other highemitting vehicles (e.g., snowmobiles). 

 Retire high-emitting vehicles from Federal fleets as quickly as possible and/or relocate highemitting vehicles to less sensitive areas until they can be retired. 

 Establish emission budgets from the transportation sector for selected FLM areas. 

 Develop mass transit systems in some NPS units (e.g., light rail in Grand Canyon NP and a bus 

system in Zion NP). 

Minor Source Strategies

 Apply RACT, BACT, LAER, best and reasonably available control measures, etc., to existing 

sources, as appropriate. 

 Go beyond conformity requirements to include the protection of AQRVs in FLM areas by 

ensuring all actions FLMs can practicably control in and near FLM areas will not cause, or 

contribute to, an adverse impact on any AQRV. 

Improved involvement with interested parties in gateway communities (those adjacent to FLM areas) 

will likely be required to ensure growth in these communities occurs in a manner that mitigates the 

impact on natural resources. These communities may need to enhance their participation in the 

planning processes of FLMs. Similarly, FLMs must participate in planning activities for public lands 

located in the FLM area and communities adjacent to FLM areas to ensure air quality concerns are 

adequately addressed. Mechanisms must be identified and developed for community involvement in 

developing, implementing, and enforcing emission management strategies for sources near and in 

FLM areas. 

Implementing strategies to achieve emission reductions in and near FLM areas will require efforts in at 

least three specific areas: 

1. FLMs should ensure that sufficient emphasis is placed in agency planning documents requiring the 

minimization of air pollution emissions from new activities or practices. 

2. FLM agencies should inventory air pollution emissions within FLM areas. After emissions have 

been quantified, FLMs, States, and adjacent communities will be able to assess the impact of these 

emissions through the use of appropriate models. Knowledge of Class I area emissions will also 

improve FLM ability to consult with States during the development and review of their SIPs 

(especially visibility SIPs). 

 

3. FLMs should cooperate with States and local communities in assessing the need for, and the 

development of, appropriate emission reduction strategies in and near FLM areas that address non-
23 

PSD sources. Without an acknowledgment from States and local communities that these sources 

may pose a threat to FLM areas and a systematic assessment of these potential impacts, current 

efforts to protect FLM area resources may be insufficient. 

c. Conformity Requirements in Nonattainment Areas 

Conformity criteria and procedures ensure that actions on lands administered by Federal agencies do 

not cause a violation of the NAAQS, increase the frequency of any standards violations, or delay 

attainment. Conformity to SIPs is only required for activities within nonattainment areas for nontransportation related sources if emissions are above de minimis levels and regionally significant. Any 

activity that represents 10 percent, or more, of the emission inventory for that pollutant in the nonattainment or maintenance area is regionally significant. Examples of actions that may require a 

conformity determination include road paving projects, ski area development, or mining. Activities 

such as prescribed fire, that are included in a conforming land management plan, are exempt from 

conformity requirements. 

The FLM should define the process to be used in conformity determinations and perform the 

conformity analysis before a project is implemented. A conformity analysis typically includes 

emission calculations, public participation, mitigation measures/implementation schedules, and 

reporting methods. The Pacific Southwest Region of the USDA/FS has published a Conformity 

Handbook for FLMs to assist in conformity compliance. In an approved Plan of Operation, FLMs can 

require monitoring. For example, in the case of Carlota Mine, located on National Forest land in 

Arizona, the USDA/FS requested additional mitigation measures to protect AQRVs in the Superstition 

Wilderness. 

Transportation projects in FLM areas classified as nonattainment are subject to a more complicated 

transportation conformity process. Consultation with State and local air quality and transportation 

agencies will be required to comply with applicable regulations.
24 

D. SUBGROUP REPORTS: 

TECHNICAL ANALYSES AND RECOMMENDATIONS 

1. SUBGROUP OBJECTIVES AND TASKS 

Subgroups were formed to address the four key issues relevant to AQRV identification and evaluation 

issues: policy (and procedures), visibility, ozone, and deposition. Each of these subgroups reviewed 

the commonalities among the FLMs then addressed the tasks assigned to them by FLAG. One of their 

first tasks was to differentiate between Phase I tasks, those which could be resolved in the short term 

without significant additional resources, and Phase II issues, those that would require a longer period 

or greater effort. 

Subgroups were asked to reach common ground among the FLMs on the issues. The intent was to 

develop, to the extent possible, consistent policies, processes, and terminology that could be used 

when identifying AQRVs and evaluating impacts on AQRVs. This involves recommending consistent 

approaches for identifying air pollution effects on AQRVs, for determining adverse impacts, and for 

attributing adverse impacts to specific pollution sources. In addition, the FLMs consider that AQRV 

protection from visibility, ozone, and deposition impacts are equally important. However, we also 

recognize that given the current state of the science, attributing adverse impacts to specific sources are 

easier to document for visibility than for deposition and ozone, and easier for deposition than ozone. 

The individual subgroup reports document the common policies, procedures, and definitions 

identified or developed during Phase I activities. The Visibility, Ozone, and Deposition subgroup 

reports are included below. The FLAG Policy Subgroup Report was used as the basis for much of the 

rest of this FLAG Phase I Report, including much of Section B. "Background" and Section C. 

"Federal Land Managers' Approach to AQRV Protection." 

2. VISIBILITY 

a. Introduction 

This chapter describes methods for analyzing the impacts on visibility from new or modified air 

pollution sources. This includes sources that fall under the purview of the Prevention of Significant 

Deterioration (PSD) regulations and sources that are being analyzed for Environmental Impact 

Statements under the National Environmental Policy Act (NEPA). The basis for some of the 

decisions outlined in this chapter is section 169A of the Clean Air Act. The opening statement of 

this section states: “Congress hereby declares as a national goal the prevention of any future, and 

the remedying of any existing, impairment of visibility in mandatory class I Federal areas which 

impairment results from manmade air pollution.” Under the regulations promulgated for visibility 

protection (40 CFR §51.301 (x)) visibility impairment is defined as “...any humanly perceptible 

change in visibility (visual range, contrast, coloration) from that which would have existed under 

natural conditions.” The remainder of this chapter describes methods that allow for new source 

growth to be analyzed against the constraint of preventing visibility impairment as defined in 40 

CFR §51.301 (x), that is, new source growth should not allow any humanly perceptible change in 

visibility as compared against natural conditions. 

There are three different visibility impact thresholds that are discussed: levels of concern, analysis 
25 

thresholds, and decision thresholds. These are all interrelated. The levels of concern are visibility 

impact levels that would alert the FLM to a need for closer scrutiny. The analysis thresholds 

parallel these levels of concern in that if visibility impacts approach the levels of concern, the FLM 

would need to see further analyses to make an informed judgement about those impacts. The 

decision thresholds correspond to the visibility impacts, below which the FLM is not likely to 

object to an increase in visibility impairing pollutants. It is important to note that the decision 

thresholds can not be absolute; the FLM is required to make a determination on a “...case-by-case 

basis taking into account the geographic extent, intensity, duration, frequency and time of visibility 

impairments...” (40 CFR §51.301 (a)). However, the decision thresholds should be useful as an 

initial benchmark for analysts to judge whether visibility impacts would likely cause the FLM to 

object to a proposed action. 

Natural Conditions

Comparing the impacts of new source growth against natural conditions implies that natural 

conditions are defined. At the time of this writing (December 2000) the EPA is working on 

defining natural conditions in support of their visibility regulations, but that work has not yet been 

completed. An estimate of natural conditions has been made (NAPAP, 1990). These estimates are 

only differentiated by the broad categories of the eastern and western United States. FLAG has 

adopted the appropriate aerosol concentrations from the NAPAP as estimates of natural conditions 

for each Class I area (Appendix 2.B). These estimates are a surrogate to be used until more 

definitive values for natural conditions are established. 

Visibility Impairment

Before proceeding with the discussion, it is useful to identify the ways that visibility impairment 

can manifest itself. First, the pollutant loading of a section of the atmosphere can become visible, 

by the contrast or color difference between a layer or plume and a viewed background, such as a 

landscape feature or the sky. The second way that visibility is impaired is a general alteration in 

the appearance of landscape features or the sky, changing the color or the contrast between 

landscape features or causing features of a view to disappear. The first phenomenon is commonly 

referred to as plume impairment, whereas the second phenomenon is sometimes referred to as 

uniform haze impairment. As plumes are transported within a stable atmospheric layer, they may 

become a layered haze. As plumes and other more diffuse emission sources are transported and 

become well mixed in the atmosphere, they may develop into a uniform haze. 

Visibility Parameters

The analysis methods for new source growth, described in this chapter, only deal with the visibility 

effects of discrete plumes and the aggregation of discrete plumes. The difference in these 

phenomena, as treated in this chapter, is whether the visibility effect is primarily seen as a section 

of the atmosphere which exhibits a change in contrast or color as compared with a viewed 

background, or whether the effect is due to an alteration of the appearance of the background 

features themselves. For the first situation, the contrast (C) and color difference index (∆E) of the 

plume and the viewing background are calculated. For the second situation, the change in 

atmospheric light extinction (∆bext), relative to natural conditions, is calculated. An approximation 

for which situation applies is the distance from the point of emission. (Distance serves as an 

indicator of where steady state conditions may apply.) The visibility impairment from sources 
26 

within 50 kilometers of a view is usually calculated using contrast and color difference, where 

visibility impairment from sources greater than 50 kilometers from a view, or the aggregation of a 

number of plumes, regardless of distance, is usually calculated using the change in light extinction. 

The distance approximation is useful for distinguishing these two phenomena; the terms “near 

field” and “distant/multi-source” are sometimes used in the remainder of this document to make 

this distinction. More information on visibility parameters can be found in Appendix 2.A. 

Levels of Concern

The crucial level of concern for visibility impairment is whether it is humanly perceptible as 

compared against natural conditions (40 CFR §51.301(x)). As noted above, different visibility 

parameters are applied for different phenomena. A summary of the thresholds of perceptibility for 

the case of a plume viewed against a background indicates that contrast values (C) of ±0.01 to 

±0.05 (note that the sign denotes whether the plume is brighter (+) or darker (-) than the 

background) are perceptible (NAPAP, 1990). A change in the color difference index (∆E) of less 

than 1 to 4 has been identified as the range of perceptibility for this parameter. The Workbook for 

Plume Visual Impact Screening and Analysis (USEPA, 1992a) suggests that a level of 0.05 for the 

absolute value of contrast (|C| = 0.05) and ∆E = 2 be used as thresholds in screening analyses; 

these levels were set in the mid-range of the perceptibility thresholds, in part, because of the 

conservative nature of the screening calculations. These levels also constitute the FLM’s level of 

concern for screening analyses of plumes viewed against a background. Under circumstances of a 

more refined analysis, |C| = 0.02 and ∆E = 1 are the levels of concern (USEPA, 1992b). These 

levels are usually applied for near field analyses where single sources are locating within 50 

kilometers of a view. 

For the case of visibility impairment which changes the appearance of a viewed background 

feature, thresholds of perceptibility, where a just noticeable change occurs in the scene, have been 

found to correspond to a change in extinction (∆bext) as low as 2% under ideal conditions, up to 

20% (NAPAP, 1990; Pitchford and Malm, 1994). A ∆bext of 5% will evoke a just noticeable 

change in most landscapes (NAPAP, 1990). The FLMs are concerned about situations where a 

change in extinction from new source growth is greater than 5% as compared against natural 

conditions. Changes in extinction greater than 10% are generally considered unacceptable by the 

FLMs and will likely raise objections to further pollutant loading without mitigation. These levels 

are usually applied for distant/multi-source analyses where sources are located more than 50 

kilometers from a view or for analyzing the visibility impairment from an aggregation of plumes 

from multiple sources, regardless of distance. 

Cumulative Analyses

A cumulative effects analysis of new source growth (defined as all PSD increment-consuming 

sources) on visibility impairment should be performed. The change in extinction (∆bext) will 

usually be the visibility parameter examined. The FLMs recognize that cumulative analyses of the 

effects of new source growth on visibility impairment have only rarely been carried out. Until 

cumulative analyses are performed for an area, the FLMs are suggesting some analysis thresholds 

to either trigger a cumulative analysis or allow a source to be permitted if its impact is below 

certain prescribed levels. 
27 

If a cumulative analysis has already been performed for the area, or if other considerations (i.e., 

NEPA, PSD increments, or other AQRV analyses) require that a cumulative analysis be performed 

for the proposed source, then the visibility impacts of the source are expected to be considered as 

part of the cumulative visibility impairment, as compared against natural conditions. When these 

conditions are met, the inclusion of the proposed source is expected regardless of the predicted 

visibility impairment of the source, unless its impacts are considered below de minimis. 

Analysis Thresholds for New Cumulative Analyses 

The analysis thresholds outlined here are interim levels to be used until such time as cumulative 

analyses are conducted for an area. Change in extinction (∆bext) is usually the visibility parameter 

analyzed for a cumulative analysis. If the visibility impact of a proposed project is below 0.4%∗

change in extinction, the impacts would be considered below de minimis and would not require 

further analysis. For situations where a cumulative visibility analysis has not been done or is not 

required because of other considerations, the following analysis thresholds will apply. If the 

visibility impact of a proposed source is less than a 5% change in extinction a cumulative analysis 

would not be expected. For visibility impairment predicted to be above 5%, but less than 10%, 

change in extinction from a proposed source, a cumulative analysis is expected. If the visibility 

impairment is predicted to be greater than 10% from a proposed source, the FLM is likely to object 

to the project regardless of other source growth, unless there is mitigation. 

Decision Thresholds 

Each determination of whether the impacts from a new source or major modification will be 

considered adverse must, by regulation, be made on a case-by-case basis (40 CFR §51.301(a)). 

Therefore, the decision thresholds specified here are strictly a guideline. More refined visibility 

analyses may indicate that the visibility parameters used (i.e., C, ∆E, ∆bext) do not adequately 

characterize the visibility for a particular situation; the FLMs will consider such information in 

making their decision. The decision thresholds parallel the FLM levels of concern. For near field 

situations where a section of the atmosphere is polluted and is viewed against a scenic background, 

screening analysis values of contrast with an absolute value less than 0.05 (|C| < 0.05) would not 

likely result in an objection by the FLM. Similarly, a value of ∆E < 2 from a screening analysis 

would not likely result in an objection. If a refined near field analysis is performed, values of 

|C| < 0.02 or ∆E < 1 would not likely result in an objection by the FLM. 

For distant or multi-source situations, if a cumulative visibility analysis has not previously been 

conducted and is not required for other analyses, a single-source change in extinction less than 5% 

would not generally trigger a need for a cumulative analysis. Under those circumstances, the FLM 

would not likely object to the proposed action. If the forecast single-source contribution to 

extinction is between 5% and 10%, or if a cumulative analyses is required or already exists, a 

special decision threshold applies. If the visibility impairment from the proposed action, in 

combination with cumulative new source growth, is less than a change in extinction of 10% for all 

time periods, the FLMs will not likely object to the proposed action. If the visibility impairment 

 

∗

 The de minimis level of 0.4% is defined as 4% of the unacceptable change in extinction (i.e., 10%), paralleling the 

discussion of significant impact levels in the proposed new source review modifications. (FR 61 38291-38293) 
28 

from the proposed action, in combination with cumulative new source growth, is greater than or 

equal to a change in extinction of 10% for any time periods, the FLMs will likely object to the 

proposed action, unless the contribution from the proposed action is less than a de minimis value of 

0.4% for these time periods. 

Relationship to Regional Haze Rule 

The FLAG recommendations are complimentary to the regional haze rule. However, the visibility 

recommendations of FLAG are intended for new source review and NEPA type applications, 

whereas the regional haze rule addresses the effects of existing sources of visibility impairment in 

conjunction with new source review. The FLAG recommendation is designed to prevent new 

sources from causing visibility impairment, and the criteria for developing these recommendations 

do not necessarily apply to existing sources. At the time of this writing, new source review is an 

ongoing effort, but it will be several years before State Implementation Plans (SIPs) under the 

regional haze rule are submitted. If the new visibility SIPs adequately account for new source 

growth, the FLMs may reconsider the FLAG recommendations. 

The visibility parameters for cumulative impact analysis, outlined here, are related to those in the 

regional haze rule. However, an assumption inherent in regional haze is that the pollution is fairly 

evenly distributed over a broad geographic extent. By contrast, the analysis techniques, described 

herein, at most deal with the aggregation of a subset of the plumes that might affect regional haze, 

but do not meet the criteria of being a regional haze. 

The levels of concern and de minimis levels described in this document were arrived at, in part, 

with the knowledge they apply to a limited number of sources under new source review and that 

the analyses are always compared to natural conditions. The de minimis levels described here 

should not be used for determining whether emissions from an existing source are reasonably 

anticipated to cause or contribute to visibility impairment. Those criteria have been laid out in the 

regulations (40 CFR §51 Subpart P Protection of Visibility) and through interpretations of those 

regulations by EPA and courts. 

While there are some distinct differences between this document and the regional haze rule, there 

are also some similarities. One of these is the need for conducting a cumulative assessment of 

visibility impairment. This will include the need for evaluating the effects of sources beyond an 

individual state’s boundaries. Therefore, it is anticipated that when modeling centers are 

established for SIP development work, the tools they use may be applicable to analyzing both 

existing impairment as well as the potential impacts of new source growth. 
29 

b. Analysis Techniques 

There are two fundamentally different approaches one could adopt to determine visibility 

impairment. One is a technically rigorous, complex, and situation-specific method, while the other 

is a more generalized approach. The more rigorous approach requires determination of particle 

concentrations and size distributions, calculation of particle growth dynamics, and application of 

Mie Theory to determine the optical characteristics of the aerosol distribution. Sophisticated 

radiative transfer models are then applied, using aerosol optical characteristics, lighting and scene 

characteristics, and spatial distribution of the pollutants to calculate the path and wavelength of 

image-forming and non-image-forming light that reaches a specific observer from all points in the 

scene being viewed. 

While such a detailed analysis may be useful for assessing specific cases, it is usually impractical 

for situations in which visibility could be experienced in a nearly infinite variety of circumstances. 

Practical limitations frequently dictate that it is more reasonable to use a generalized approach to 

determine the change in extinction by using bulk-averaged aerosol-specific extinction efficiencies 

rather than trying to reproduce the complex optical phenomena that may occur in the atmosphere. 

Consequently, FLAG recommends the generalized approach for determining the effects on 

visibility from a proposed new source's emissions. The procedure is to estimate the atmospheric 

concentrations of visibility impairing pollutants, apply representative visibility parameters, 

calculate the change from specified reference levels, and compare this change with prescribed 

threshold values. 

FLAG is using estimates of natural conditions as reference levels for Class I visibility analyses. 

Comparison with natural conditions will help ensure that those conditions will not be impaired in 

keeping with Section 169A of the CAA. Because of the different requirements of the two modeling 

approaches discussed below, natural conditions must be expressed using two different metrics: 

• Standard visual range (visual range adjusted to a Rayleigh condition of 10 Mm-1), for near field 

modeling. Present EPA guideline visibility models traditionally accept visibility conditions 

expressed in these terms. 

• Extinction, for distant/multi-source modeling. Visibility conditions should be expressed in 

terms of the averaged extinction efficiencies of the individual atmospheric constituents that 

comprise the total extinction. The relative humidity effects of the hygroscopic particles must 

be accounted for when the change in extinction is calculated. 

Information needed to calculate the above indices is provided in Appendix 2.B for all 156 Class I 

areas for which visibility is an important attribute. If estimates are needed for Class II areas, the 

FLM can provide them. 

c. Air Quality Models and Visibility Assessment Procedures 

The modeling discussion will be divided into two parts to address the very different requirements 

for 1) near field modeling where plumes or layers are compared against a viewing background and 

2) distant/multi-source modeling for plumes and aggregations of plumes that affect the general 

appearance of a scene. Note that both of the above analyses might apply depending on the source’s 
30 

proximity to all portions of the Class I area or multiple Class I areas. 

 

Near Field Analysis Technique for Analyzing Plumes or Layers Viewed Against a Background 

The Model (Near Field – Steady State Conditions Applicable)

EPA has recommended a methodology to assess impacts due to coherent plumes. A guideline, for 

when these steady state conditions apply, is the distance from the source to the view of concern. 

This technique is usually applied for sources locating less than 50 km from a Class I area. 

Applicants must model their potential plume impacts using the screening model, VISCREEN 

(USEPA, 1992a), or, if the next level of analysis is called for, PLUVUE II (USEPA 1992b and 

1996c). Both of these models use steady-state, gaussian-based plume dispersion techniques to 

calculate one-hour concentrations within an elevated plume. These two models calculate the 

change in the color difference index (∆Ε) and contrast between the plume and the viewing 

background. Values of ∆Ε and plume contrast are based on the concentrations of fine primary 

particulates (including sulfates), nitrogen dioxide (NO2), and the geometry of the observer, target, 

plume, and the position of the sun. PLUVUE II also allows consideration of the effects of 

secondarily formed sulfates. Plume contrast results from an increase or decrease in light 

transmitted from the viewing background through the plume to the observer. The specifics of the 

emission scenarios and plume/observer geometries for modeling should be selected in consultation 

with the appropriate FLM. At the present time there is no recommended procedure for conducting 

analyses of multiple sources with these modeling tools, so multiple coherent plumes must be 

treated individually, or combined into a representative single source if reasonable. 

The Recommended Prescription (Near Field – Steady State Conditions)

Until better modeling tools are available, FLAG recommends using the present EPA techniques for 

plume visual impact screening analyses (USEPA 1992a). However, unlike those procedures, which 

suggest the use of current average annual visibility conditions, FLAG recommends that the visual 

range corresponding to natural conditions be used to generate the hourly estimates of ∆E and plume 

contrast. FLAG recommends this change in order for the analysis technique to be consistent with the 

national visibility goal. For screening-level analyses, FLAG recommends the use of the annual 

average reconstructed natural conditions given in the last column in Table 2.B-1 in Appendix 2.B. 

The table entry gives the specified reference level (including the effects of relative humidity) 

expressed in Mm-1. The conversion to standard visual range can be made using Equation 1 in 

Appendix 2.A. For the refined analyses, the reconstructed natural condition is derived from the 

relative humidity used in the modeling, the corresponding relative humidity adjustment factor 

(Table 2.A-1), and estimated natural aerosol concentrations (Table 2.B-1). 

If a screening analysis of a new or modified source can demonstrate that its emissions will not cause 

a plume with any hourly estimates of ∆E greater than or equal to 2.0, or the absolute value of the 

contrast values (|C|) greater than or equal to 0.05, the FLM is not likely to object to the issuance of 

the PSD permit based on near field visibility impacts and no further near field visibility analyses will 

be requested. More refined analyses (i.e., PLUVUE II) would be undertaken if the above conditions 

are not met and would be compared against lower levels of concern; the FLM would not likely object 

if ∆E < 1.0 and |C| < 0.02. 
31 

If the estimated plume parameters exceed the aforementioned values, the FLM would rely on a caseby-case effects-based test (NPS 1993), taking into account magnitude, frequency, duration, and other 

factors, to decide whether to make an adverse impact determination. 

Distant/Multi-Source Techniques for Analyzing Whether a Plume or an Aggregation of Plumes 

Alters the General Appearance of a Scene 

This application is generally more complex than the near field, coherent plume modeling analyses 

and the guidance from EPA is less definitive, though it is evolving. The modeling system must 

include the capability to assess single and multiple sources in a temporally and spatially varying 

meteorological domain, accommodate modeling domains measuring hundreds of kilometers, 

include rough and complex terrain, provide pollutant concentration estimates for averaging times 

from one-hour to annual, and address inert and secondarily formed pollutants and dry and wet 

deposition. In the early 1990s the FLMs and the EPA recognized the need for a consistent, 

technically credible technique to estimate contributions to air quality of multiple new sources 

locating more than 50 km from Class I areas. Toward that end, the Interagency Workgroup on Air 

Quality Modeling (IWAQM) was established to develop a modeling protocol for this application. 

FLAG proposes to rely on the IWAQM recommendations and modeling guidance for long range 

pollutant transport (present guidance, USEPA 1998∗

). This technique is usually applied when 

sources are located more than 50 kilometers from portions of a Class I area, when an aggregation of 

plumes may impact an area, or when the assumptions inherent in steady state visibility models do 

not apply. 

The Model (Distant/Multi-Source)

Revised IWAQM guidance (USEPA 1998*

) recommends non-steady state air quality modeling 

systems for screening and refined analyses. The IWAQM recommendations are adaptations and 

refinements of the CALPUFF dispersion modeling system, including the CALMET meteorological 

model (USEPA 1996a, http://www.src.com/calpuff/calpuff1.htm). This modeling system consists 

of diagnostic meteorological models, a gaussian puff dispersion model with algorithms for 

chemical transformation, wet and dry deposition, and complex terrain, and a post processor 

(CALPOST) for calculating concentration and deposition fields and visibility impacts. 

The modeling systems/techniques outlined in this recommendation provide ground level 

concentrations of visibility impairing pollutants. These concentrations can then be used to 

calculate the extinction due to these pollutants, using the relationships outlined in Appendix 2.A. 

The results should be compared against a reference level derived from aerosol information (relative 

humidity adjusted hygroscopic and non-hygroscopic concentrations plus Rayleigh extinction) given 

in Appendix 2.B for each Class I area. This reference level is a function of relative humidity. To 

achieve the best temporal and spatial resolution, relative humidity data included in the 

meteorological data base of the air quality model and the data provided in Table 2.A-1 is the 

preferred basis for making the necessary calculation of the relative humidity adjustment term f(RH) 

for refined visibility analyses. The approach, for screening level analyses, is to use the quarterly 

averaged reference levels given in Table 2.B-1 that are based on spatially interpolated seasonal 

relative humidity values and empirically derived f(RH) adjustment factors (IMPROVE 2000). In 

 

∗

 At the time of this writing, USEPA is considering similar procedures for incorporation into the Guideline on Air 

Quality Models (40 CFR §51 Appendix W). This should be consulted for the latest information. 
32 

either approach, the same relative humidity adjustment factor, f(RH), is applied to determine both 

the reference level and the effect of the incremental increase associated with the new source(s). An 

example model application is given in Appendix 2.C. 

For the purposes of the following prescription, FLAG recommends basing the analyses on block 24-

hour averages (i.e., daily) of modeled visibility. The 24-hour average was selected over the 1-hour 

average time because: 

• Our confidence in model performance for 24-hours is higher than for shorter time periods. 

• The combined visibility effect of emissions from multiple sources transported over long distances 

is better represented over 24-hours than for shorter time periods. 

• It avoids detailed day/night visibility considerations. 

• It avoids developing and implementing site-specific, complex visibility analytical methods that are 

not available at this time (see discussion under Analysis Techniques). 

The Recommended Prescription (Distant/Multi-Source)

The FLMs are concerned with the cumulative effects of new source growth on visibility; 

cumulative analyses need to be conducted. The FLMs recognize, however, that few cumulative 

visibility analyses have been done, therefore, the following prescription is suggested. If a 

cumulative analysis has not been performed for an area and if a single project’s visibility 

impairment, compared against natural conditions, is below certain analysis thresholds, then the 

FLMs are not likely to object to the project or ask that a cumulative analysis be performed before 

the project proceeds. If a cumulative analysis has already been done or if a cumulative analysis is 

required because of other considerations (i.e., increment consumption, NEPA, or other AQRVs), or 

if the analysis thresholds are exceeded, then the impacts of the proposed project are expected to be 

considered as part of a cumulative visibility analysis. 

The prescription is as follows: 

1. Calculate the single-source contribution. Compare results with the distant/multi-source Decision 

Threshold. 

• Determine whether a cumulative analysis has been done for the Class I area(s) in question, 

and if it has been done, use the input files from the cumulative analysis to perform this step. 

• If the estimated increase in visibility impairment attributed to the proposed project is 

≥ 10%, compared against natural conditions, for at least one modeled day, then the FLM 

will consider the magnitude, frequency, duration, and other factors to assess the impact, but 

is likely to object to the issuance of the permit. 

• If the estimated increase in visibility impairment attributed to the proposed project is <10%, 

then the analysis should proceed to the next step (Note that if the single-source contribution 

is always <0.4%, no further analyses are required). 

2. If a cumulative analysis does not exist, compare the single-source contribution with distant/multisource Analysis Threshold and assess the need for a cumulative analysis. 
33 

• If a cumulative analysis does not exist, and if there are no other requirements for a 

cumulative analysis, and if a new or modified source can demonstrate that its contribution 

to a change in extinction is <5.0%, compared against natural conditions, for all days, then 

the FLM is not likely to object to the issuance of the PSD permit based on visibility 

impacts. 

• If the single-source contribution to a change in extinction is ≥ 5.0% or if a cumulative 

analysis already exists or is required for some other reason, then the analysis should 

proceed to the next step and estimate its contribution to cumulative impacts. 

3. Conduct a cumulative analysis and compare results with cumulative, distant/multi-source 

Decision Threshold. 

• If cumulative change in extinction is ≥10%, for all modeled block 24-hour periods, and the 

new source contributes at least a 0.4% change in extinction to any of these periods, then the 

FLM will consider the magnitude, frequency, duration, and other factors to assess the impact, 

but is likely to object to the issuance of the permit. 

• If cumulative modeling results indicate that the effects from the combined sources are 

expected to cause a change in extinction that is < 10%, for all modeled block 24-hour 

periods, then the FLM is not likely to object to the issuance of the permit. 

This prescription is portrayed schematically in Figure V-1. 
34 

 Figure V-1. Prescription for visibility assessment for distant/multi-source applications 

 (source greater than or equal to 50 km from the Class I area) 

Prescription for New Source 

Review Visibility Analysis 

(Distant/Multi-source) 

Single-source 

contribution to 

change in 

extinction ≥

10.0% 

?

FLM likely to object 

to the permit 

FLM not likely to 

object to the permit 

Has a cumulative analysis been 

conducted (or has the source 

triggered a need for a cumulative 

impact analysis) or is its 

contribution to extinction ≥ 5.0% 

?

Conduct cumulative 

visibility analysis of PSD 

increment consuming 

sources 

Cumulative change in 

extinction ≥10% and 

single-source 

contribution ≥ 0.4% 

? 

FLM likely to object 

to the permit 

Yes

No 

No 

Yes

Yes

No 
35 

d. Summary 

FLAG has provided guidance in the form of recommendations, specific prescriptions, and 

interpretation of results for assessing visibility impacts near Class I areas (although this guidance is 

generally applicable to Class II areas, as well). The guidance addresses assessments for sources 

proposed for locations near and at large distances from these areas. It also recommends 

impairment thresholds and identifies the conditions for which cumulative analyses of all incrementconsuming sources would be necessary. The key components of the recommendations are 

highlighted below. 

In general, FLAG recommends that an applicant: 

• Consult with the appropriate regulatory agency and with the FLM for the affected Class I area(s) 

or other affected area for confirmation of preferred procedures and for the need for a cumulative 

analysis. 

• Obtain FLM recommendation for the specified reference levels (estimate of natural conditions) 

and, if applicable, FLM recommended plume/observer geometries and model receptor locations. 

• Apply the applicable EPA Guideline, steady-state models for regions within the Class I area that 

are affected by plumes or layers that are viewed against a background (generally within 50 km of 

the source). 

Calculate hourly estimates of ∆E and plume contrast, with respect to natural conditions, and 

compare these estimates with the thresholds given in Section D.2.c. 

• For regions of the Class I area where visibility impairment from the source would cause a general 

alteration of the appearance of the scene (generally 50 km or more away from the source or from 

the interaction of the emissions from multiple sources), apply a non-steady-state air quality model 

with chemical transformation capabilities (refer to IWAQM guidance documents), which yields 

ambient concentrations of visibility-impairing pollutants. At each Class I receptor: 

Calculate the change in extinction due to the source being analyzed, compare these changes 

with the reference conditions, and compare these results with the thresholds given in Section 

D.2.c. 

If necessary, calculate the cumulative change in extinction due to new source growth. 
36 

Appendix 2.A 

Visibility Parameters 

Visibility is usually characterized by either visual range (VR) (the greatest distance that a large 

dark object can be seen) or by the light-extinction coefficient (bext) (the attenuation of light per unit 

distance due to scattering and absorption by gases and particles in the atmosphere) (IMPROVE, 

1996). Under certain assumed conditions, these parameters are inversely related to each other by 

Equation 1; a long visual range corresponds to a low extinction. Visual range is useful for safety 

reasons such as to direct aircraft traffic near airports, but is not particularly useful for assessing the 

quality of scenic vistas. Nonetheless, visual range remains a useful measure for describing visibility, 

especially for communication with the general public. The dimensions of VR are length and the 

dimensions of bext are 1/length. Visual range is usually expressed in kilometers. The extinction 

coefficient is sometimes expressed as “inverse kilometers” (km-1) or as “inverse megameters” 

(Mm-1) (the reciprocal of 1 million meters). If bext is expressed in Mm-1 the coefficient 3.912 

becomes 3912 as in Equation 1. 

Equation 1. Relationship between visual range and light-extinction coefficient. 

Other visibility parameters frequently used include ∆E and contrast. These metrics relate to the 

color difference or contrast, respectively, of a plume or haze with respect to some viewing 

background. 

Calculating the Extinction Coefficient

Visibility is degraded by visible light scattered into and out of the line of sight and by light absorbed 

along the line of sight. Light extinction is the sum of light scattering and absorption, and is usually 

quantified using the light extinction coefficient (bext). Extinction can be measured directly or it can be 

calculated from representative aerosol measurements. Using a generalized approach to estimating 

visibility effects, one can calculate the extinction coefficient as the sum of its parts, i.e., bext = bscat + 

babs, where bscat and babs are the light scattering and absorption coefficients. The light scattering and 

absorption coefficients can be further broken down by their respective components. The scattering 

coefficient is affected by light scattering (Rayleigh scattering (bRay)) from air molecules and from 

particle scattering (bsp); the particles can be natural aerosol or result from air pollutants. The 

absorption coefficient is affected by gaseous absorption (bag) and particulate absorption (bap). 

Nitrogen dioxide is the only major light-absorbing gas in the lower atmosphere; it generally does not 

affect hazes, although it can be an important element in a coherent plume assessment. Therefore, only 

particle absorption is considered in the suggested far-field visibility analyses, although nitrogen 

dioxide absorption should be considered when this technique is applied to sources in the near field. 

Particle scattering can be broken down by the contributions of different particulate species. It has 

been convenient to consider the scattering coefficients of fine particles (PM2.5) (particles with mass 

mean diameters less than or equal to 2.5 μm) and coarse particles (mass mean diameters greater 

than 2.5μm but less than or equal to 10μm). The fine particle scattering coefficient can be further 

defined by the sum of the scattering coefficient due to sulfates (bSO4 ), nitrates (bNO3), organic 

b (Mm )

3912

b (km )

3.912 VR(km) 1

ext

1

ext

− − = =
37 

aerosols (bOC), and soil (bSoil); the coarse scattering coefficient (bCoarse) is not refined any further. 

Thus the particle scattering coefficient (bsp) can be expressed as in Equation 2. 

Equation 2. Components of particle scattering. 

Each of the particle scattering coefficients can be related to the mass of the components using the 

relationships in Equation 3. 

Equation 3. Relationship between particle scattering and mass of each species. 

The quantities in brackets are the masses expressed in μg/m3

. (It is assumed that the forms of the 

SO4

=

 and NO3

-

 are ammonium sulfate [(NH4)2SO4] and ammonium nitrate [NH4NO3].) The 

numeric coefficients are the “dry” scattering efficiencies (m2

/g). The term f(RH) is the relative 

humidity adjustment factor. The extinction coefficients are in Mm-1. If the “dry” scattering 

efficiencies are divided by 1000 (i.e., 0.003 instead of 3) the resultant extinction coefficients will 

be in km-1. 

Particle absorption (bap) is primarily due to elemental carbon (soot). Similarly, absorption by gases 

(bag) is primarily from nitrogen dioxide (NO2). For purposes of analyzing the effects of soot or 

NO2 on visibility in a modeling analysis, the relationships in Equation 4 should be used. Again, the 

quantities in brackets are the masses of elemental carbon or nitrogen dioxide in μg/m3

 and 10 and 

0.17 are the extinction efficiencies. Nitrogen dioxide absorption is usually only an issue in the 

near-field, therefore, it is usually not considered in an analysis for distant sources. 

bap = 10[EC] 

bag = 0.17[NO2] 

Equation 4. Relationship between particle absorption and elemental carbon. 

The total atmospheric extinction can be expressed as in Equation 5, where bRay is the Rayleigh 

scattering component, which is assumed to be 10 Mm-1. 

bext = bSO4 + bNO3 +bOC + bsoil + bCoarse + bap (+ bag)

* + bRay 

Equation 5. Components of Extinction (*bag is usually only considered in near-field analyses). 

bsp = bSO4 + bNO3 + bOC + bSoil + bCoarse

[ ]

[ ]

[ ]

[ ]

b 0.6 [ ] Coarse Mass

b 1 Soil

b 4 OC

b 3 NH NO f(RH)

b 3 (NH ) SO f(RH)

Coarse

Soil

OC

NO3 4 3

SO4 4 2 4

=

=

=

=

=
38 

To the extent that a source contributes to the formation of some of these constituents, those 

contributions can be summed to yield the source’s contribution to extinction. This will be 

discussed in more detail below. 

Examination of Equation 3 reveals that the sulfate and nitrate components of the extinction 

coefficient are dependent upon relative humidity. These aerosols are hygroscopic and the addition 

of water enhances their scattering efficiencies. It is sometimes convenient to consider the sulfate 

and nitrate components of extinction separately from the remaining components of Equation 5 and 

to keep the relative humidity adjustment factor (f(RH)) separate. Equation 5 can then be rewritten 

as in Equation 6, where bhygro is the combined extinction coefficient of sulfate and nitrate, 

excluding the relative humidity adjustment factor, and bnon-hygro is the sum of bOC, bSoil, bCoarse, bap, 

and bag. 

bext = bhygrof(RH) + bnon-hygro + bRay 

Equation 6. Extinction coefficient expressed as the sulfate and nitrate contribution 

(bhygro =3[(NH4)2SO4 + NH4NO3]) and non-hygroscopic components (bnon-hygro = 

bOC+bSoil+bCoarse+bap+bag). 

The relative humidity adjustment factor requires some further explanation. The variation of the effect 

of relative humidity on the extinction efficiency, f(RH), of sulfates and nitrates is given numerically in 

Table 2.B-1. As can be seen, the effect of relative humidity on the extinction efficiency of these 

aerosols is non-linear, and is several times greater at higher relative humidity than at lower humidity. 

FLAG proposes that the relative humidity adjustment to the “dry” scattering efficiencies 

(unadjusted for relative humidity) for hygroscopic particles are made as follow: 

• The preferred alternative is to apply day-by-day f(RH) adjustment factors to the analysis. For this 

alternative hourly relative humidity data are needed. Hourly f(RH) values should be averaged to 

generate a 24-hour relevant f(RH) factor. FLAG recommends, however, that if the hourly relative 

humidity exceeds 98%, that it be rolled back to 98%, so that there will be no f(RH) factors applied 

that are greater than f(98). 

• For screening analyses the adjustment factor can be based on historic averages of f(RH) for the 

Class I area(s) of concern (Table 2.B-1).
39 

Table 2.A-1. f(RH) values for various values of relative humidity∗

RH(%) f(RH) RH(%) f(RH) RH(%) f(RH) RH(%) f(RH) 

1 1.0 26 1.0 51 1.2 76 2.3 

2 1.0 27 1.0 52 1.3 77 2.4 

3 1.0 28 1.0 53 1.3 78 2.5 

4 1.0 29 1.0 54 1.3 79 2.6 

5 1.0 30 1.0 55 1.3 80 2.7 

6 1.0 31 1.0 56 1.3 81 2.8 

7 1.0 32 1.0 57 1.3 82 3.0 

8 1.0 33 1.0 58 1.4 83 3.1 

9 1.0 34 1.0 59 1.4 84 3.2 

10 1.0 35 1.0 60 1.4 85 3.4 

11 1.0 36 1.0 61 1.5 86 3.6 

12 1.0 37 1.1 62 1.5 87 3.8 

13 1.0 38 1.1 63 1.5 88 4.0 

14 1.0 39 1.1 64 1.6 89 4.4 

15 1.0 40 1.1 65 1.7 90 4.7 

16 1.0 41 1.1 66 1.7 91 5.3 

17 1.0 42 1.1 67 1.7 92 5.9 

18 1.0 43 1.1 68 1.8 93 7.0 

19 1.0 44 1.2 69 1.9 94 8.4 

20 1.0 45 1.2 70 1.9 95 9.8 

21 1.0 46 1.2 71 2.0 96 12.4 

22 1.0 47 1.2 72 2.0 97 15.1 

23 1.0 48 1.2 73 2.1 98 18.1 

24 1.0 49 1.2 74 2.1 99 18.1♦

25 1.0 50 1.2 75 2.2 100 18.1♦

 

 

∗

 The values in Table 2.A-1 are only appropriate for averaging times of 1 hour or less. 

♦ The values for 99% and 100% RH are rolled back to the value for 98%. 
40 

Appendix 2.B 

Estimate of Natural Conditions 

Table 2.B-1 provides natural background estimates for visibility reference levels for each Class I 

area; these will serve until better estimates of natural conditions are available. The estimates for 

natural background aerosol concentrations provided in the State of Science and Technology No.24 

(NAPAP, 1990), shown in Table 2.B-2 provide the basis for these estimates. The seasonal and annual 

means for the relative humidity adjustment factor f(RH) given in the table are computed using 

spatially interpolated and quarterly averaged National Weather Service relative humidity data and the 

following empirical relationships derived from site-specific relative humidity collected at some Class 

I areas (IMPROVE 2000). 

2 f (RH) = 0.34 + 0.59(1/(1− RH)) + 0.09(1/(1− RH)) (Annual) 

f (RH) = 0.35 + 0.82(1/(1− RH)) (Winter) 

2 f (RH) = −0.01+ 0.78(1/(1− RH)) + 0.08(1/(1− RH)) (Spring) 

f (RH) = −0.19 + 0..99(1/(1− RH)) (Summer) 

2 f (RH) = −0.25 +1.02(1/(1− RH)) + 0.01(/(1− RH)) (Fall) 

For annual, winter (Dec, Jan, Feb), spring (Mar, Apr, May), summer (Jun, July, Aug), and fall 

(Sep, Oct, Nov), respectively. The visibility impairment (bext) due to this assumed distribution of 

background aerosol is calculated using Equation 6, Appendix 2.A. 

The source of the relative humidity data is 10 years of monthly averaged historic National Weather 

Service data (over 250 sites) spatially interpolated and gridded (0.25 degree grid size) and further 

interpolated to specific Class I areas. The annual and quarterly means are shown in Figure 2.B-1. 
41 

Average Annual Relative Humidity Values 

N 

A 0 500 1000 1500 Miles 

Legend 

Class I Art as 

70 RH Valuts 

lnttrpolaud) 

{\J RH Contours 

Projection Albers Equal-Data SoLrces 

RH data from EPA An

NWS data (report 

Class I area centroids 

Air Resources Div

Date of map 6/20/2000 

Cartographer K. Clifford 
42 

Average Winter Relative Humidity Values 

N 

A 0 500 1000 1500 Miles 

68 

Legen

Class I .Ar

70 RH Valuts 

(lntorpol<U

(\J RHComou

Projection Albers Equ

Data Sources 

RH data from EPA 

NWS data (repo

Class I area centro

Air Resources D

Date of map 6/16/200

Cartographer K. Cliffo
43 

Average Spring Relative Humidity Values 

N 

A 0 500 1000 1500 Miles 

64 

Legen

Class I Ar

70 RH Valuts 

(lntorpol<U

('J RH Comou

Projection Albers Equa

Data Sources 

RH data from EPA A

NWS data (repo

Class I area centroid

Air Resources D

Date of map 6/20/2000 

Cartographer K. Cliffo
44 

Average Summer Relative Humidity Values 

N 

A 0 500 1000 1500 Miles 

Legend 

Class I Art a

70 RH Values 

(Jntupo Jau d

(\J RH Comour

Projection Albers Equal

Data Sources 

RH data from EPA A

NWS data (report 

Class I area centroids 

Air Resources Div

Date of map 6/20/2000 

Cartographer K. Clifford 
45 

N 

A 

Average Fall Relative Humidity Values 

Miles 

70 

Legend 

Class I Art a

70 RH Vtb.lts 

(lntupol<U

(\J RH Comour

Projection Albers EquaData Sources 

RH data from EPA A

NWS data (repor

Class I area centroid

Air Resources D

Date of map 6/20/2000 

Cartographer K. Cliffor
46 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Acadia NP Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.2 11.4 21.4 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

Agua Tibia W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 2.4 5.9 15.9 

 Spring 0.6 4.5 10.0 2.6 6.1 16.1 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Alpine Lakes W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 4.5 7.2 17.2 

 Spring 0.6 4.5 10.0 3.3 6.5 16.5 

 Summer 0.6 4.5 10.0 2.7 6.1 16.1 

 Fall 0.6 4.5 10.0 5.1 7.6 17.6 

Anaconda – Pintlar W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 3.7 6.7 16.7 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 3.1 6.4 16.4 

Ansel Adams W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.0 6.3 16.3 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Arches NP Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 3.3 6.5 16.5 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.4 5.3 15.3 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Badlands NP (W) Annual 0.6 4.5 10.0 2.6 6.1 16.1 

 Winter 0.6 4.5 10.0 3.1 6.4 16.4 

 Spring 0.6 4.5 10.0 2.6 6.1 16.1 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 2.8 6.2 16.2 
47 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Bandelier NM (W) Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.0 5.7 15.7 

Big Bend NP Annual 0.6 4.5 10.0 2.1 5.8 15.8 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.9 5.6 15.6 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Black Canyon NP Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 1.6 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Bob Marshall W Annual 0.6 4.5 10.0 2.7 6.1 16.1 

 Winter 0.6 4.5 10.0 3.9 6.8 16.8 

 Spring 0.6 4.5 10.0 2.5 6.0 16.0 

 Summer 0.6 4.5 10.0 2.0 5.7 15.7 

 Fall 0.6 4.5 10.0 3.5 6.6 16.6 

Bosque del Apache W Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.2 5.8 15.8 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Boundary Waters Annual 0.9 8.5 10.0 3.3 11.5 21.5 

Canoe Area W Winter 0.9 8.5 10.0 3.6 11.7 21.7 

 Spring 0.9 8.5 10.0 2.6 10.8 20.8 

 Summer 0.9 8.5 10.0 3.4 11.6 21.6 

 Fall 0.9 8.5 10.0 3.9 12.0 22.0 

Breton Island W Annual 0.9 8.5 10.0 3.8 11.9 21.9 

 Winter 0.9 8.5 10.0 3.4 11.6 21.6 

 Spring 0.9 8.5 10.0 4.0 12.1 22.1 

 Summer 0.9 8.5 10.0 4.1 12.2 22.2 

 Fall 0.9 8.5 10.0 3.6 11.7 21.7 
48 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Bridger W Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 1.9 5.6 15.6 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.4 5.9 15.9 

Brigantine W Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.8 11.0 21.0 

 Spring 0.9 8.5 10.0 2.9 11.1 21.1 

 Summer 0.9 8.5 10.0 3.4 11.5 21.5 

 Fall 0.9 8.5 10.0 3.0 11.2 21.2 

Bryce Canyon NP Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 1.4 5.4 15.4 

 Summer 0.6 4.5 10.0 1.4 5.3 15.3 

 Fall 0.6 4.5 10.0 2.0 5.7 15.7 

Cabinet Mountains W Annual 0.6 4.5 10.0 2.7 6.1 16.1 

 Winter 0.6 4.5 10.0 4.2 7.0 17.0 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 1.9 5.7 15.7 

 Fall 0.6 4.5 10.0 3.8 6.8 16.8 

Caney Creek W Annual 0.9 8.5 10.0 3.1 11.3 21.3 

 Winter 0.9 8.5 10.0 3.1 11.3 21.3 

 Spring 0.9 8.5 10.0 3.3 11.5 21.5 

 Summer 0.9 8.5 10.0 3.0 11.2 21.2 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

Canyonlands NP Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 3.2 6.4 16.4 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Cape Romain W Annual 0.9 8.5 10.0 3.3 11.5 21.5 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 3.3 11.4 21.4 

 Summer 0.9 8.5 10.0 3.9 12.0 22.0 

 Fall 0.9 8.5 10.0 3.3 11.5 21.5 
49 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Capitol Reef NP Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 3.0 6.3 16.3 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Caribou W Annual 0.6 4.5 10.0 2.3 5.9 15.9 

 Winter 0.6 4.5 10.0 3.6 6.6 16.6 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.7 6.1 16.1 

Carlsbad Caverns NP Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.9 5.6 15.6 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Chassahowitzka W Annual 0.9 8.5 10.0 3.9 12.0 22.0 

 Winter 0.9 8.5 10.0 3.4 11.6 21.6 

 Spring 0.9 8.5 10.0 3.7 11.8 21.8 

 Summer 0.9 8.5 10.0 4.1 12.2 22.2 

 Fall 0.9 8.5 10.0 3.9 12.0 22.0 

Chiricahua NM (W) Annual 0.6 4.5 10.0 1.6 5.4 15.4 

 Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.2 5.2 15.2 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.6 5.5 15.5 

Chiricahua W Annual 0.6 4.5 10.0 1.5 5.4 15.4 

 Winter 0.6 4.5 10.0 2.1 5.7 15.7 

 Spring 0.6 4.5 10.0 1.2 5.2 15.2 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.6 5.5 15.5 

Cohutta W Annual 0.9 8.5 10.0 3.2 11.4 21.4 

 Winter 0.9 8.5 10.0 3.0 11.2 21.2 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.6 11.7 21.7 

 Fall 0.9 8.5 10.0 3.3 11.4 21.4 
50 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Crater Lake NP Annual 0.6 4.5 10.0 3.3 6.5 16.5 

 Winter 0.6 4.5 10.0 4.7 7.3 17.3 

 Spring 0.6 4.5 10.0 3.1 6.4 16.4 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 4.4 7.2 17.2 

Craters of the Annual 0.6 4.5 10.0 2.2 5.8 15.8 

Moon NM (W) Winter 0.6 4.5 10.0 3.8 6.8 16.8 

 Spring 0.6 4.5 10.0 1.9 5.7 15.7 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.8 6.2 16.2 

Cucamonga W Annual 0.6 4.5 10.0 2.3 5.9 15.9 

 Winter 0.6 4.5 10.0 2.4 5.9 15.9 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Desolation W Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 3.3 6.5 16.5 

 Spring 0.6 4.5 10.0 1.8 5.6 15.6 

 Summer 0.6 4.5 10.0 1.6 5.4 15.4 

 Fall 0.6 4.5 10.0 2.4 6.0 16.0 

Diamond Peak W Annual 0.6 4.5 10.0 3.5 6.6 16.6 

 Winter 0.6 4.5 10.0 4.9 7.4 17.4 

 Spring 0.6 4.5 10.0 3.2 6.4 16.4 

 Summer 0.6 4.5 10.0 2.3 5.9 15.9 

 Fall 0.6 4.5 10.0 4.8 7.4 17.4 

Dolly Sods W Annual 0.9 8.5 10.0 3.1 11.3 21.3 

 Winter 0.9 8.5 10.0 3.0 11.2 21.2 

 Spring 0.9 8.5 10.0 3.0 11.2 21.2 

 Summer 0.9 8.5 10.0 3.4 11.6 21.6 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Dome Land W Annual 0.6 4.5 10.0 1.9 5.7 15.7 

 Winter 0.6 4.5 10.0 2.4 6.0 16.0 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.7 15.7 
51 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Eagle Cap W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 4.3 7.1 17.1 

 Spring 0.6 4.5 10.0 2.2 5.8 15.8 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 3.5 6.6 16.6 

Eagles Nest W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 1.9 5.6 15.6 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Emigrant W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.2 6.4 16.4 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Everglades NP Annual 0.9 8.5 10.0 3.9 12.0 22.0 

 Winter 0.9 8.5 10.0 3.6 11.8 21.8 

 Spring 0.9 8.5 10.0 3.7 11.9 21.9 

 Summer 0.9 8.5 10.0 3.8 12.0 22.0 

 Fall 0.9 8.5 10.0 4.0 12.1 22.1 

Fitzpatrick W Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 1.9 5.7 15.7 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.4 6.0 16.0 

Flat Tops W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.6 6.1 16.1 

 Spring 0.6 4.5 10.0 1.8 5.6 15.6 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Galiuro W Annual 0.6 4.5 10.0 1.6 5.5 15.5 

 Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.2 5.2 15.2 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.7 5.5 15.5 
52 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Gates of the Annual 0.6 4.5 10.0 2.4 5.9 15.9 

Mountains W Winter 0.6 4.5 10.0 3.1 6.4 16.4 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.8 6.2 16.2 

Gearhart Mountain W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 4.0 6.9 16.9 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 3.2 6.4 16.4 

Gila W Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.2 5.8 15.8 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Glacier NP Annual 0.6 4.5 10.0 2.8 6.2 16.2 

 Winter 0.6 4.5 10.0 2.8 6.2 16.2 

 Spring 0.6 4.5 10.0 2.5 6.0 16.0 

 Summer 0.6 4.5 10.0 2.1 5.8 15.8 

 Fall 0.6 4.5 10.0 3.8 6.8 16.8 

Glacier Peak W Annual 0.6 4.5 10.0 3.8 6.8 16.8 

 Winter 0.6 4.5 10.0 4.4 7.2 17.2 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.8 6.2 16.2 

 Fall 0.6 4.5 10.0 5.1 7.6 17.6 

Goat Rocks W Annual 0.6 4.5 10.0 3.6 6.6 16.6 

 Winter 0.6 4.5 10.0 4.6 7.3 17.3 

 Spring 0.6 4.5 10.0 3.2 6.4 16.4 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 5.0 7.5 17.5 

Grand Canyon NP Annual 0.6 4.5 10.0 1.6 5.5 15.5 

 Winter 0.6 4.5 10.0 2.4 5.9 15.9 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.4 5.3 15.3 

 Fall 0.6 4.5 10.0 1.7 5.5 15.5 
53 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Grand Teton NP Annual 0.6 4.5 10.0 2.1 5.8 15.8 

 Winter 0.6 4.5 10.0 3.0 6.3 16.3 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 

Great Gulf W Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.8 11.0 21.0 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.3 11.5 21.5 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

Great Sand Annual 0.6 4.5 10.0 2.0 5.7 15.7 

Dunes NM (W) Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Great Smoky Annual 0.9 8.5 10.0 3.2 11.4 21.4 

Mountains NP Winter 0.9 8.5 10.0 3.0 11.2 21.2 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.6 11.8 21.8 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Guadalupe Annual 0.6 4.5 10.0 1.8 5.6 15.6 

Mountains NP Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.9 5.6 15.6 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Hells Canyon W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 4.3 7.1 17.1 

 Spring 0.6 4.5 10.0 2.2 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 3.5 6.6 16.6 

Hercules Glades W Annual 0.9 8.5 10.0 3.1 11.3 21.3 

 Winter 0.9 8.5 10.0 3.2 11.4 21.4 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.2 11.4 21.4 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 
54 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Hoover W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.1 6.4 16.4 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Isle Royale NP Annual 0.9 8.5 10.0 3.5 11.6 21.6 

 Winter 0.9 8.5 10.0 3.4 11.6 21.6 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.6 11.7 21.7 

 Fall 0.9 8.5 10.0 4.1 12.2 22.2 

James River Face W Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 3.0 11.2 21.2 

 Summer 0.9 8.5 10.0 3.5 11.7 21.7 

 Fall 0.9 8.5 10.0 3.0 11.2 21.2 

Jarbidge W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.5 6.6 16.6 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.3 5.3 15.3 

 Fall 0.6 4.5 10.0 2.4 6.0 16.0 

John Muir W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Joshua Tree NM (W) Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 2.0 5.7 15.7 

 Fall 0.6 4.5 10.0 2.0 5.7 15.7 

Joyce Kilmer Annual 0.9 8.5 10.0 3.2 11.4 21.4 

Slickrock W Winter 0.9 8.5 10.0 3.0 11.2 21.2 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.6 11.7 21.7 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 
55 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Kaiser W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.0 6.3 16.3 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 

Kalmiopsis W Annual 0.6 4.5 10.0 3.4 6.5 16.5 

 Winter 0.6 4.5 10.0 4.7 7.3 17.3 

 Spring 0.6 4.5 10.0 3.2 6.4 16.4 

 Summer 0.6 4.5 10.0 2.3 5.9 15.9 

 Fall 0.6 4.5 10.0 4.4 7.2 17.2 

Kings Canyon NP Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.8 6.2 16.2 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

La Garita W p 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 1.6 5.5 15.5 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Lassen Volcanic NP Annual 0.6 4.5 10.0 2.3 5.9 15.9 

 Winter 0.6 4.5 10.0 3.6 6.7 16.7 

 Spring 0.6 4.5 10.0 2.1 5.7 15.7 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.7 6.1 16.1 

Lava Beds NM (W) Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 3.9 6.9 16.9 

 Spring 0.6 4.5 10.0 2.2 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 3.1 6.4 16.4 

Linville Gorge W Annual 0.9 8.5 10.0 3.2 11.3 21.3 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.7 11.8 21.8 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 
56 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Lostwood W Annual 0.6 4.5 10.0 2.9 6.2 16.2 

 Winter 0.6 4.5 10.0 3.2 6.4 16.4 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 2.3 5.9 15.9 

 Fall 0.6 4.5 10.0 3.5 6.6 16.6 

Lye Brook W Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.3 11.4 21.4 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

Mammoth Cave NP Annual 0.9 8.5 10.0 3.2 11.4 21.4 

 Winter 0.9 8.5 10.0 3.3 11.5 21.5 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.4 11.6 21.6 

 Fall 0.9 8.5 10.0 3.3 11.5 21.5 

Marble Mountain W Annual 0.6 4.5 10.0 3.1 6.3 16.3 

 Winter 0.6 4.5 10.0 4.4 7.1 17.1 

 Spring 0.6 4.5 10.0 2.9 6.2 16.2 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 3.8 6.8 16.8 

Maroon Bells Annual 0.6 4.5 10.0 1.9 5.7 15.7 

Snowmass W Winter 0.6 4.5 10.0 2.6 6.0 16.0 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

Mazatzal W Annual 0.6 4.5 10.0 1.6 5.5 15.5 

 Winter 0.6 4.5 10.0 2.2 5.8 15.8 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.7 5.5 15.5 

Medicine Lake W Annual 0.6 4.5 10.0 2.8 6.2 16.2 

 Winter 0.6 4.5 10.0 3.2 6.4 16.4 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 3.5 6.6 16.6 
57 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Mesa Verde NP Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.6 6.1 16.1 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

Mingo W Annual 0.9 8.5 10.0 3.2 11.3 21.3 

 Winter 0.9 8.5 10.0 3.3 11.4 21.4 

 Spring 0.9 8.5 10.0 3.0 11.2 21.2 

 Summer 0.9 8.5 10.0 3.3 11.4 21.4 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Mission Mountains W Annual 0.6 4.5 10.0 2.7 6.1 16.1 

 Winter 0.6 4.5 10.0 4.0 6.9 16.9 

 Spring 0.6 4.5 10.0 2.5 6.0 16.0 

 Summer 0.6 4.5 10.0 2.0 5.7 15.7 

 Fall 0.6 4.5 10.0 3.6 6.7 16.7 

Mokelumne W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.3 6.5 16.5 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.4 5.9 15.9 

Moosehorn W Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.2 21.2 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.2 11.4 21.4 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Mount Adams W Annual 0.6 4.5 10.0 3.6 6.7 16.7 

 Winter 0.6 4.5 10.0 4.7 7.3 17.3 

 Spring 0.6 4.5 10.0 3.2 6.4 16.4 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 5.0 7.5 17.5 

Mount Baldy W Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 
58 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Mount Hood W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 4.7 7.3 17.3 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.6 6.1 16.1 

 Fall 0.6 4.5 10.0 5.2 7.6 17.6 

Mount Jefferson W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 4.8 7.4 17.4 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 5.2 7.6 17.6 

Mount Rainier NP Annual 0.6 4.5 10.0 3.8 6.8 16.8 

 Winter 0.6 4.5 10.0 4.6 7.3 17.3 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.7 6.1 16.1 

 Fall 0.6 4.5 10.0 5.2 7.6 17.6 

Mount Washington W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 4.8 7.4 17.4 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 5.1 7.6 17.6 

Mount Zirkel W Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 1.9 5.6 15.6 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Mountain Lakes W Annual 0.6 4.5 10.0 2.8 6.2 16.2 

 Winter 0.6 4.5 10.0 4.4 7.2 17.2 

 Spring 0.6 4.5 10.0 2.6 6.1 16.1 

 Summer 0.6 4.5 10.0 1.9 5.7 15.7 

 Fall 0.6 4.5 10.0 3.8 6.8 16.8 

North Absoraka W Annual 0.6 4.5 10.0 2.2 5.8 15.8 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 2.1 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 
59 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

North Cascades NP Annual 0.6 4.5 10.0 3.8 6.8 16.8 

 Winter 0.6 4.5 10.0 4.2 7.0 17.0 

 Spring 0.6 4.5 10.0 3.4 6.5 16.5 

 Summer 0.6 4.5 10.0 2.8 6.2 16.2 

 Fall 0.6 4.5 10.0 5.1 7.6 17.6 

Okefenokee W Annual 0.9 8.5 10.0 3.5 11.7 21.7 

 Winter 0.9 8.5 10.0 3.2 11.3 21.3 

 Spring 0.9 8.5 10.0 3.4 11.5 21.5 

 Summer 0.9 8.5 10.0 3.9 12.0 22.0 

 Fall 0.9 8.5 10.0 3.6 11.7 21.7 

Olympic NP Annual 0.6 4.5 10.0 4.5 7.2 17.2 

 Winter 0.6 4.5 10.0 4.4 7.2 17.2 

 Spring 0.6 4.5 10.0 4.1 7.0 17.0 

 Summer 0.6 4.5 10.0 3.4 6.5 16.5 

 Fall 0.6 4.5 10.0 5.8 8.0 18.0 

Otter Creek W Annual 0.9 8.5 10.0 3.2 11.3 21.3 

 Winter 0.9 8.5 10.0 3.0 11.2 21.2 

 Spring 0.9 8.5 10.0 3.0 11.2 21.2 

 Summer 0.9 8.5 10.0 3.5 11.6 21.6 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Pasayten W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 3.8 6.8 16.8 

 Spring 0.6 4.5 10.0 3.3 6.5 16.5 

 Summer 0.6 4.5 10.0 2.7 6.1 16.1 

 Fall 0.6 4.5 10.0 5.0 7.5 17.5 

Pecos W Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.0 5.7 15.7 

Petrified Forest NP Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 1.9 5.6 15.6 
60 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Pine Mountain W Annual 0.6 4.5 10.0 1.6 5.5 15.5 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.7 5.5 15.5 

Pinnacles NM (W) Annual 0.6 4.5 10.0 2.4 5.9 15.9 

 Winter 0.6 4.5 10.0 3.4 6.5 16.5 

 Spring 0.6 4.5 10.0 2.1 5.8 15.8 

 Summer 0.6 4.5 10.0 2.0 5.7 15.7 

 Fall 0.6 4.5 10.0 2.7 6.1 16.1 

Point Reyes NS (W) Annual 0.6 4.5 10.0 3.0 6.3 16.3 

 Winter 0.6 4.5 10.0 3.9 6.9 16.9 

 Spring 0.6 4.5 10.0 2.7 6.1 16.1 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 3.1 6.4 16.4 

Presidential Range Annual 0.9 8.5 10.0 3.0 11.2 21.2 

Dry River W Winter 0.9 8.5 10.0 2.8 11.0 21.0 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.3 11.5 21.5 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

Rawah W Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Red Rock Lakes W Annual 0.6 4.5 10.0 2.2 5.8 15.8 

 Winter 0.6 4.5 10.0 3.2 6.4 16.4 

 Spring 0.6 4.5 10.0 2.1 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.7 6.1 16.1 

Redwood NP Annual 0.6 4.5 10.0 4.2 7.0 17.0 

 Winter 0.6 4.5 10.0 4.6 7.3 17.3 

 Spring 0.6 4.5 10.0 4.3 7.1 17.1 

 Summer 0.6 4.5 10.0 3.2 6.4 16.4 

 Fall 0.6 4.5 10.0 4.6 7.3 17.3 
61 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Rocky Mountain NP Annual 0.6 4.5 10.0 2.1 5.7 15.7 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

Saguaro NP Annual 0.6 4.5 10.0 1.6 5.4 15.4 

 Winter 0.6 4.5 10.0 2.1 5.7 15.7 

 Spring 0.6 4.5 10.0 1.2 5.2 15.2 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.6 5.5 15.5 

Salt Creek W Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.9 5.6 15.6 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

San Gabriel W Annual 0.6 4.5 10.0 2.4 5.9 15.9 

 Winter 0.6 4.5 10.0 2.4 5.9 15.9 

 Spring 0.6 4.5 10.0 2.4 6.0 16.0 

 Summer 0.6 4.5 10.0 2.4 5.9 15.9 

 Fall 0.6 4.5 10.0 2.2 5.8 15.8 

San Gorgonio W Annual 0.6 4.5 10.0 2.2 5.8 15.8 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 2.2 5.8 15.8 

 Summer 0.6 4.5 10.0 2.1 5.8 15.8 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

San Jacinto W Annual 0.6 4.5 10.0 2.3 5.9 15.9 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 2.2 5.8 15.8 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

San Pedro Parks W Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.4 6.0 16.0 

 Spring 0.6 4.5 10.0 1.5 5.4 15.4 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.0 5.7 15.7 
62 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

San Rafael W Annual 0.6 4.5 10.0 2.6 6.1 16.1 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 2.6 6.0 16.0 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 

Sawtooth W Annual 0.6 4.5 10.0 2.2 5.8 15.8 

 Winter 0.6 4.5 10.0 4.0 6.9 16.9 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.9 6.2 16.2 

Scapegoat W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 3.5 6.6 16.6 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 1.9 5.6 15.6 

 Fall 0.6 4.5 10.0 3.1 6.3 16.3 

Selway – Bitterroot W Annual 0.6 4.5 10.0 2.6 6.0 16.0 

 Winter 0.6 4.5 10.0 4.0 6.9 16.9 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 3.4 6.5 16.5 

Seney W Annual 0.9 8.5 10.0 3.6 11.8 21.8 

 Winter 0.9 8.5 10.0 3.7 11.8 21.8 

 Spring 0.9 8.5 10.0 2.9 11.1 21.1 

 Summer 0.9 8.5 10.0 3.6 11.7 21.7 

 Fall 0.9 8.5 10.0 4.2 12.3 22.3 

Sequoia NP Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 1.8 5.6 15.6 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

Shenandoah NP Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 2.9 11.1 21.1 

 Summer 0.9 8.5 10.0 3.4 11.6 21.6 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 
63 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Shining Rock W Annual 0.9 8.5 10.0 3.2 11.4 21.4 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.7 11.9 21.9 

 Fall 0.9 8.5 10.0 3.2 11.3 21.3 

Sierra Ancha W Annual 0.6 4.5 10.0 1.6 5.5 15.5 

 Winter 0.6 4.5 10.0 2.2 5.8 15.8 

 Spring 0.6 4.5 10.0 1.3 5.3 15.3 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.7 5.5 15.5 

Sipsey W Annual 0.9 8.5 10.0 3.3 11.5 21.5 

 Winter 0.9 8.5 10.0 3.2 11.4 21.4 

 Spring 0.9 8.5 10.0 3.3 11.4 21.4 

 Summer 0.9 8.5 10.0 3.5 11.7 21.7 

 Fall 0.9 8.5 10.0 3.3 11.5 21.5 

South Warner W Annual 0.6 4.5 10.0 2.1 5.8 15.8 

 Winter 0.6 4.5 10.0 3.6 6.7 16.7 

 Spring 0.6 4.5 10.0 1.9 5.6 15.6 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.6 6.1 16.1 

St. Marks W Annual 0.9 8.5 10.0 3.6 11.8 21.8 

 Winter 0.9 8.5 10.0 3.2 11.4 21.4 

 Spring 0.9 8.5 10.0 3.5 11.7 21.7 

 Summer 0.9 8.5 10.0 4.0 12.1 22.1 

 Fall 0.9 8.5 10.0 3.6 11.8 21.8 

Strawberry Mountain 

W 

Annual 0.6 4.5 10.0 2.6 6.1 16.1 

 Winter 0.6 4.5 10.0 4.4 7.1 17.1 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 3.7 6.7 16.7 

Superstition W Annual 0.6 4.5 10.0 1.6 5.4 15.4 

 Winter 0.6 4.5 10.0 2.1 5.8 15.8 

 Spring 0.6 4.5 10.0 1.2 5.2 15.2 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 1.6 5.5 15.5 
64 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Swanquarter W Annual 0.9 8.5 10.0 3.3 11.5 21.5 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 3.3 11.4 21.4 

 Summer 0.9 8.5 10.0 3.8 11.9 21.9 

 Fall 0.9 8.5 10.0 3.2 11.4 21.4 

Sycamore Canyon W Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.3 5.9 15.9 

 Spring 0.6 4.5 10.0 1.4 5.3 15.3 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Teton W Annual 0.6 4.5 10.0 2.1 5.8 15.8 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 

Theodore Roosevelt 

NP 

Annual 0.6 4.5 10.0 2.7 6.1 16.1 

 Winter 0.6 4.5 10.0 3.7 6.7 16.7 

 Spring 0.6 4.5 10.0 2.5 6.0 16.0 

 Summer 0.6 4.5 10.0 2.1 5.8 15.8 

 Fall 0.6 4.5 10.0 3.2 6.4 16.4 

Thousand Lakes W Annual 0.6 4.5 10.0 2.3 5.9 15.9 

 Winter 0.6 4.5 10.0 3.7 6.7 16.7 

 Spring 0.6 4.5 10.0 2.1 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.8 6.2 16.2 

Three Sisters W Annual 0.6 4.5 10.0 3.7 6.7 16.7 

 Winter 0.6 4.5 10.0 4.9 7.4 17.4 

 Spring 0.6 4.5 10.0 3.4 6.6 16.6 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 5.1 7.6 17.6 

U.L. Bend W Annual 0.6 4.5 10.0 2.4 5.9 15.9 

 Winter 0.6 4.5 10.0 3.3 6.5 16.5 

 Spring 0.6 4.5 10.0 2.3 5.9 15.9 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.8 6.2 16.2 
65 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Upper Buffalo W Annual 0.9 8.5 10.0 3.1 11.3 21.3 

 Winter 0.9 8.5 10.0 3.2 11.4 21.4 

 Spring 0.9 8.5 10.0 3.1 11.3 21.3 

 Summer 0.9 8.5 10.0 3.2 11.4 21.4 

 Fall 0.9 8.5 10.0 3.2 11.3 21.3 

Ventana W Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 3.4 6.5 16.5 

 Spring 0.6 4.5 10.0 2.2 5.8 15.8 

 Summer 0.6 4.5 10.0 2.1 5.8 15.8 

 Fall 0.6 4.5 10.0 2.7 6.1 16.1 

Voyageurs NP Annual 0.9 8.5 10.0 3.4 11.5 21.5 

 Winter 0.9 8.5 10.0 3.7 11.8 21.8 

 Spring 0.9 8.5 10.0 2.6 10.8 20.8 

 Summer 0.9 8.5 10.0 3.4 11.6 21.6 

 Fall 0.9 8.5 10.0 4.1 12.2 22.2 

Washakie W Annual 0.6 4.5 10.0 2.1 5.8 15.8 

 Winter 0.6 4.5 10.0 2.8 6.2 16.2 

 Spring 0.6 4.5 10.0 2.0 5.7 15.7 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 

Weminuche W Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.5 6.0 16.0 

 Spring 0.6 4.5 10.0 1.6 5.4 15.4 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

West Elk W Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.6 6.1 16.1 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.6 5.5 15.5 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 

Wheeler Peak W Annual 0.6 4.5 10.0 1.9 5.6 15.6 

 Winter 0.6 4.5 10.0 2.4 5.9 15.9 

 Spring 0.6 4.5 10.0 1.6 5.5 15.5 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 2.1 5.8 15.8 
66 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

White Mountain W Annual 0.6 4.5 10.0 1.8 5.6 15.6 

 Winter 0.6 4.5 10.0 2.2 5.8 15.8 

 Spring 0.6 4.5 10.0 1.4 5.4 15.4 

 Summer 0.6 4.5 10.0 1.8 5.6 15.6 

 Fall 0.6 4.5 10.0 1.8 5.6 15.6 

Wichita Mountain W Annual 0.6 4.5 10.0 2.6 6.1 16.1 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 2.8 6.2 16.2 

 Summer 0.6 4.5 10.0 2.5 6.0 16.0 

 Fall 0.6 4.5 10.0 2.6 6.1 16.1 

Wind Cave NP Annual 0.6 4.5 10.0 2.5 6.0 16.0 

 Winter 0.6 4.5 10.0 2.9 6.2 16.2 

 Spring 0.6 4.5 10.0 2.5 6.0 16.0 

 Summer 0.6 4.5 10.0 2.1 5.7 15.7 

 Fall 0.6 4.5 10.0 2.6 6.1 16.1 

Wolf Island W Annual 0.9 8.5 10.0 3.5 11.6 21.6 

 Winter 0.9 8.5 10.0 3.1 11.3 21.3 

 Spring 0.9 8.5 10.0 3.3 11.5 21.5 

 Summer 0.9 8.5 10.0 3.9 12.0 22.0 

 Fall 0.9 8.5 10.0 3.6 11.7 21.7 

Yellowstone NP Annual 0.6 4.5 10.0 2.2 5.8 15.8 

 Winter 0.6 4.5 10.0 3.0 6.3 16.3 

 Spring 0.6 4.5 10.0 2.1 5.8 15.8 

 Summer 0.6 4.5 10.0 1.7 5.5 15.5 

 Fall 0.6 4.5 10.0 2.5 6.0 16.0 

Yolla Bolly – Annual 0.6 4.5 10.0 2.6 6.1 16.1 

Middle Eel W Winter 0.6 4.5 10.0 3.8 6.8 16.8 

 Spring 0.6 4.5 10.0 2.4 5.9 15.9 

 Summer 0.6 4.5 10.0 2.0 5.7 15.7 

 Fall 0.6 4.5 10.0 3.0 6.3 16.3 

Yosemite NP Annual 0.6 4.5 10.0 2.0 5.7 15.7 

 Winter 0.6 4.5 10.0 3.1 6.4 16.4 

 Spring 0.6 4.5 10.0 1.7 5.5 15.5 

 Summer 0.6 4.5 10.0 1.5 5.4 15.4 

 Fall 0.6 4.5 10.0 2.3 5.9 15.9 
67 

Site Season Components of Dry

Extinction (Mm-1) f(RH) 

Particle 

bext 

w/f(RH) 

(Mm-1) 

Reference 

Level 

(Mm-1) 

 Hygro Non 

Hygro Rayleigh 

Zion NP Annual 0.6 4.5 10.0 1.7 5.5 15.5 

 Winter 0.6 4.5 10.0 2.7 6.1 16.1 

 Spring 0.6 4.5 10.0 1.4 5.3 15.3 

 Summer 0.6 4.5 10.0 1.3 5.3 15.3 

 Fall 0.6 4.5 10.0 1.9 5.6 15.6 

Seasonal RH data not available; contact FLM 

Bering Sea W 0.6 4.5 10.0 Contact the FLM 

Denali NP 0.6 4.5 10.0 Contact the FLM 

Haleakala NP 0.6 4.5 10.0 Contact the FLM 

Hawaii Volcanoes NP 0.6 4.5 10.0 Contact the FLM 

Roosevelt Campobello IP 0.9 8.5 10.0 Contact the FLM 

Simeonof W 0.6 4.5 10.0 Contact the FLM 

Tuxedni W 0.6 4.5 10.0 Contact the FLM 

Virgin Islands NP 0.9 8.5 10.0 Contact the FLM 

Not included: 

Rainbow Lakes 

Bradbury Bay 
68 

Table 2.B-2 Estimated Annual Average Natural Background Levels of Aerosols 

Particulate Aerosol Component Annual Average Concentration 

East (μg/m3

) West (μg/m3) 

 

Sulfates (as ammonium sulfate) 0.2 0.1 

Ammonium Nitrate 0.1 0.1 

Organics 1.5 0.5 

Elemental Carbon 0.02 0.02 

Soil Dust 0.5 0.5 

Coarse 3.0 3.0 

Taken from NAPAP 1990. West refers to those States beyond the first tier of States west of the 

Mississippi River. 
69 

Appendix 2.C 

Example Problem 

Example applications for coherent plumes that are viewed against a scenic background are provided 

in the Workbook for Plume Visual Impact Screening and Analysis (USEPS, 1992a), so no specific 

example needs to be supplied here. The analysis of a plume or aggregation of plumes that affects the 

appearance of a scene does involve some new concepts, so an example application is being provided. 

The example is given for two cases, first for a general model application where a visibility post 

processor is not available, and a second case for the CALMET/CALPUFF/CALPOST modeling 

system. 

General Model Application 

For the purposes of general application, let us assume that a dispersion model has been run and 

yielded daily (24-hour) concentrations of SO4

=

 (sulfate) and soot (elemental carbon). From these 

concentrations the analyst can calculate a change in extinction from some specified reference level 

using the procedures given in Appendix 2.A. The first step is to calculate the visibility reference 

level for the Class I area of interest from the information provided in Appendix 2.B. Then, one 

calculates the new source’s contribution to extinction and the expected change in extinction from 

the reference level. This example will only address one 24-hour time period. The calculation 

would, of course, have to be repeated for the other 24-hour time periods as well as, accounting for 

the seasonal differences. 

Calculation of the Reference Level

The determination of the reference level for a single 24-hour period in January visibility condition 

can be made by examining the example table below (for an actual case, the applicant would turn to 

Appendix 2.B). While the reference extinction for Acadia NP is provided in the table (21.1Mm-1), 

it is useful to go through the calculation to see how to apply the different numbers in the table. 

Site Season Components of Dry 

Extinction (Mm-1) 

Particle bext

w/f(RH) (Mm-1) 

Reference 

Level (Mm-1) 

 Hygro Non Hygro Rayleigh 

f(RH)

bref

Acadia 

NP 

Annual 0.9 8.5 10.0 3.0 11.2 21.2 

 Winter 0.9 8.5 10.0 2.9 11.1 21.1 

 Spring 0.9 8.5 10.0 2.8 11.0 21.0 

 Summer 0.9 8.5 10.0 3.2 11.4 21.4 

 Fall 0.9 8.5 10.0 3.1 11.3 21.3 

The reference extinction (bref), expressed in the form of Equation 6 (Appendix 2.A) would be 

bref = 0.9 f(RH) + 8.5 + 10.0 (see Equation 6, Appendix 2.A). The f(RH) term in the example table 

(for January) is 2.9, yielding an extinction coefficient of 21.1 Mm-1. If one were using site specific, 

hourly relative humidity data, one would have to calculate the average f(RH) for that 24-hour 

period. To do this, one needs to look up the f(RH) value corresponding to each hour’s relative 

humidity in Table 2.A-1 (Appendix 2.A) and take the average of those f(RH) values. One can not

take the average of the relative humidity and look up the f(RH) in the table; that would yield an 
70 

incorrect result. (Similarly, the f(RH) values shown in the example table and in Appendix 2.B are 

generated using annual and seasonal average relative humidity estimates and the empirical curve 

for f(RH) given in IMPROVE 2000. Annual and seasonal averages of f(RH) do not directly 

correspond to the relative humidity values in Table 2.A-1.) 

Calculation of Single-Source Contribution 

In a typical modeling analysis, IWAQM recommends, and the FLMs endorse, the use of five years 

of meteorological data. This will produce a corresponding number of block 24-hour averaging 

periods, which will each need to be compared with the reference condition. 

Again for purposes of illustration we will only show the calculation of extinction for one modeled 

24-hour period in January. This calculation would then have to be repeated for all other 24-hour 

periods. For this example we will assume that the sources in the analysis contributed 0.3 μg/m3

 of 

sulfate (SO4

=

) and 0.10 μg/m3 of soot (elemental carbon), 24-hour average. The first step is to 

convert the mass of SO4

=

 to ammonium sulfate ((NH4)2SO4), which is accomplished by multiplying 

by the ratio of the molecular weights of (NH4)2SO4 to SO4

=

, which is 1.375. This yields a 

concentration of (NH4)2SO4 of 0.4 μg/m3

. This is then multiplied by the “dry” scattering efficiency 

of (NH4)2SO4 (which is 3, from Appendix 2.A, Equation 3), yielding an extinction coefficient for 

the sulfate of 1.2 Mm-1; the relative humidity adjustment has not yet been applied. 

In this example our modeling does not require any conversion of the mass of soot, so we will just 

multiply the soot concentration (0.10 μg/m3

) by the extinction efficiency of elemental carbon 

(which is 10, from Appendix 2.A, Equation 4). This yields an extinction coefficient of 1.0 Mm-1. 

Therefore, following the form of Equations 3 and 5 (Appendix 2.A), the source contribution would 

be: 

bsource = 1.2 f(RH) + 1.0 

A representative relative humidity adjustment term, f(RH), must be applied. It is important that the 

same adjustment be made to both the source contribution to extinction and the reference level. For 

a screening level analysis, the relative humidity adjustment factors listed in Appendix 2.B can be 

applied to the source contributions. For example, if we are analyzing for Acadia NP, the average 

winter f(RH) is 2.9. With the winter quarterly average relative humidity adjustment factor (f(RH)) 

of 2.9, bsource would be 4.5 Mm-1. 

Calculation of the Change in Extinction

The resulting percent change in extinction is found from: 

∆bext = (bsource/bref) × 100% 

For the example here, bsource = 4.5 Mm-1 and bref = 22.1 Mm-1, yielding ∆bext = 20%. This 

calculation must be repeated for each 24-hour averaging period. To portray the frequency, 

magnitude, and geographic extent of expected impairment, this calculation will have to be repeated 

for all days and many receptors in the modeling domain. FLAG expects a robust selection of model 

receptor locations in the Class I area be included in the analyses, i.e., one receptor representing the 

entire area, or just the nearest boundary, will not be sufficient. 
71 

Example using the CALMET/CALPUFF/CALPOST modeling system

For the refined analysis, it is necessary to calculate the change in extinction for the relative 

humidity conditions on a specific day. To accomplish this, the representative, hourly RH values for 

this day need to be obtained. For each hour, the corresponding f(RH) must be obtained from Table 

2.A-1. These f(RH) values are then averaged together. These calculations would have to be 

repeated for each 24-hour average concentration, at each receptor, in the analysis, using the 

corresponding average f(RH), and be applied to both the aerosol data in Table 2.B-1 (to determine 

the reference level) and the source contribution to extinction. 

In the case of a CALPUFF application, the post-processor, CALPOST, has been set up to directly 

calculate the combined visibility effects from different visibility impairing pollutants. Refer to 

Figure 2.C-1 for an example of the visibility parameters to set in the CALPOST input file. Most of 

the parameters set in CALPOST are application specific. The pollutants in the example are sulfate 

and soot (elemental carbon). CALPOST allows for the specification of sulfate (SO4), but not 

elemental carbon in the source portion of the visibility calculation. (This should be rectified in the 

next update of the modeling system.) Therefore elemental carbon will be modeled as PM fine 

(PMF). In CALPOST the variables LVSO4 and LVPMF are set to true. Since elemental carbon is 

being modeled as PMF, the extinction efficiency for PMF must be set to that for elemental carbon 

(EEPMF = 10.0). FLAG is recommending that the default f(RH) values in Appendix 2.B be used 

for screening analyses for each Class I area. Therefore, MVISBK would be set to 6. When 

MVISBK is set to 6, RHFAC would be set to the f(RH) value in Appendix 2.B or in this example, 

it would be set to 2.9 for the winter months (Dec, Jan, Feb). CALPOST does not explicitly allow 

for the input of the hygroscopic and non-hygroscopic components to extinction at this time; it only 

allows for the input of the concentrations of particulate species. To properly input the components 

to extinction, the hygroscopic component of extinction is divided by 3 (the extinction efficiency of 

sulfate and nitrate) and is input to the variable BKSO4. In this example the hygroscopic 

component of extinction is 0.9; after dividing by 3 we get a value of 0.3, which is input to 

CALPOST (BKSO4 = 0.3). For the non-hygroscopic component, enter its value into the variable 

BKSOIL (BKSOIL = 8.5) (also make sure that EESOIL is set to 1.0). All other background 

concentrations must be set to zero (0.0). Finally, a value for the extinction due to Rayleigh 

scattering must be entered (BEXTRAY = 10.0). 

If MVISBK=2 (hour-by-hour calculation of f(RH)) in the above example, the hour-by-hour relative 

humidity values from CALMET would be used to calculate the 24-hour average extinction, rather 

than the long-term average f(RH) values supplied in Appendix 2.B. The only modification to the 

input would be that the value of RHMAX (set to 98.0 in the example) would be used to cap the 

maximum f(RH) used in the averages, and the value of RHFAC would not be used. A “vis.dat” file 

(not shown in Figure 2.C-1) would also be specified. It must be generated when CALPUFF is run. 
72 

Figure 2.C-1. Segment of CALPOST input file corresponding to example problem. 

---------------------------------------------------------------------------

INPUT GROUP: 2 -- Visibility Parameters (ASPEC = VISIB) 

-------------- 

 Maximum relative humidity (%) used in particle growth curve 

 (RHMAX) -- Default: 98 ! RHMAX = 98.0 ! 

 Modeled species to be included in computing the light extinction 

 Include SULFATE? (LVSO4) -- Default: T ! LVSO4 = T ! 

 Include NITRATE? (LVNO3) -- Default: T ! LVNO3 = F ! 

 Include ORGANIC CARBON? (LVOC) -- Default: T ! LVOC = F ! 

 Include COARSE PARTICLES? (LVPMC) -- Default: T ! LVPMC = F ! 

 Include FINE PARTICLES? (LVPMF) -- Default: T ! LVPMF = T ! 

 And, when ranking for TOP-N, TOP-50, and Exceedance tables, 

 Include BACKGROUND? (LVBK) -- Default: T ! LVBK = T ! 

 Species name used for particulates in MODEL.DAT file 

 COARSE (SPECPMC) -- Default: PMC ! SPECPMC = PMC ! 

 FINE (SPECPMF) -- Default: PMF ! SPECPMF = PMF ! 

Extinction Efficiency (1/Mm per ug/m**3) 

---------------------------------------- 

 MODELED particulate species: 

 PM COARSE (EEPMC) -- Default: 0.6 ! EEPMC = 0.6 ! 

 PM FINE (EEPMF) -- Default: 1.0 ! EEPMF = 10.0 ! 

 BACKGROUND particulate species: 

 PM COARSE (EEPMCBK) -- Default: 0.6 ! EEPMCBK = 0.6 ! 

 Other species: 

 AMMONIUM SULFATE (EESO4) -- Default: 3.0 ! EESO4 = 3.0 ! 

 AMMONIUM NITRATE (EENO3) -- Default: 3.0 ! EENO3 = 3.0 ! 

 ORGANIC CARBON (EEOC) -- Default: 4.0 ! EEOC = 4.0 ! 

 SOIL (EESOIL)-- Default: 1.0 ! EESOIL = 1.0 ! 

 ELEMENTAL CARBON (EEEC) -- Default: 10. ! EEEC = 10.0 ! 

Set RHMAX = 98.0 (for MVISBK=2) 

Set the flags for the pollutants modeled. In the 

example problem SO4 and EC (Modeled as PMF) 

Note: in the example problem, the source’s elemental carbon (EC) 

is modeled as PMFINE (PMF). To calculate the extinction for EC 

as PMF the variable EEPMF needs to be reset to 10.0 
73 

 Figure 2.C-1 (Cont). Segment of CALPOST input file corresponding to example problem. 

Background Extinction Computation 

--------------------------------- 

 Method used for background light extinction 

 (MVISBK) -- Default: 6 ! MVISBK = 2 ! 

 1 = Supply single light extinction and hygroscopic fraction 

IWAQM (1993) RH adjustment applied to hygroscopic 

background 

 and modeled sulfate and nitrate 

 2 = Compute extinction from speciated PM measurements (A) 

 - Hourly RH adjustment applied to observed and modeled 

 sulfateand nitrate 

 - RH factor is capped at RHMAX 

 3 = Compute extinction from speciated PM measurements (B) 

 - Hourly RH adjustment applied to observed and modeled 

 sulfate and nitrate 

 - Receptor-hour excluded if RH>RHMAX 

 - Receptor-day excluded if fewer than 6 valid receptor-hours 

 4 = Read hourly transmissometer background extinction 

 measurements 

 - Hourly RH adjustment applied to modeled sulfate and 

 nitrate 

 - Hour excluded if measurement invalid (missing, 

 interference, or large RH) 

 - Receptor-hour excluded if RH>RHMAX 

 - Receptor-day excluded if fewer than 6 valid receptor-hours 

 5 = Read hourly nephelometer background extinction measurements 

 - Rayleigh extinction value (BEXTRAY) added to measurement 

 - Hourly RH adjustment applied to modeled sulfate and 

 nitrate 

 - Hour excluded if measurement invalid (missing, 

 interference, or large RH) 

 - Receptor-hour excluded if RH>RHMAX 

 - Receptor-day excluded if fewer than 6 valid receptor-hours 

 6 = Compute extinction from speciated PM measurements 

 - FLAG RH adjustment factor applied to observed and 

 modeled sulfate and nitrate 

For Screening Analysis MVISBK = 6 

Set RHFAC below 

For Refined Analysis use MVISBK = 2 

Specify a “vis.dat” file in CALPUFF 
74 

Figure 2.C-1 (Cont). Segment of CALPOST input file corresponding to example problem. 

 Additional inputs used for MVISBK = 6: 

 -------------------------------------- 

 Extinction coefficients for hygroscopic species (modeled and 

 background) are computed using a monthly RH adjustment factor 

 in place of an hourly RH factor (VISB.DAT file is NOT needed). 

 Enter the 12 monthly factors here (RHFAC). Month 1 is January. 

 (RHFAC) -- No default ! RHFAC = 2.9, 2.9, 2.8, 2.8, 

 2.8, 3.2, 3.2, 3.2, 

 3.1, 3.1, 3.1, 2.9 ! 

 Additional inputs used for MVISBK = 2,3,6: 

 ---------------------------------------- 

 Background extinction coefficients are computed from monthly 

 CONCENTRATIONS of ammonium sulfate (BKSO4), ammonium nitrate (BKNO3), 

 coarse particulates (BKPMC), organic carbon (BKOC), soil (BKSOIL), 

and 

 elemental carbon (BKEC). Month 1 is January. 

 (ug/m**3) 

 (BKSO4) -- No default ! BKSO4 = 0.3, 0.3, 0.3, 0.3, 

 0.3, 0.3, 0.3, 0.3, 

 0.3, 0.3, 0.3, 0.3 ! 

 (BKNO3) -- No default ! BKNO3 = 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0 ! 

 (BKPMC) -- No default ! BKPMC = 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0 ! 

 (BKOC) -- No default ! BKOC = 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0 ! 

 (BKSOIL) -- No default ! BKSOIL= 8.5, 8.5, 8.5, 8.5, 

 8.5, 8.5, 8.5, 8.5, 

 8.5, 8.5, 8.5, 8.5 ! 

 (BKEC) -- No default ! BKEC = 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0, 

 0.0, 0.0, 0.0, 0.0 ! 

 Additional inputs used for MVISBK = 2,3,5,6: 

 ------------------------------------------ 

 Extinction due to Rayleigh scattering is added (1/Mm) 

 (BEXTRAY) -- Default: 10.0 ! BEXTRAY = 10.0 ! 

For screening analysis set monthly 

f(RH) values from Appendix 2.B 

Background extinction values (Appendix 2.B) set to: 

BKSO4 = Hygroscopic / 3 

BKSOIL = Non-Hygroscopic 

BKNO3, BKPMC, BKOC, BKEC = 0.0 
75 

3. OZONE 

a. Introduction 

Ozone is a toxic air pollutant that is formed on warm, sunny days when its precursors nitrogen 

oxides (NOx) and volatile organic compounds (VOC) react in the presence of sunlight. Because 

ozone is a regional pollutant, precursor sources both near and far from FLM areas can contribute to 

ozone formation. 

High ozone exposure can harm human health (U.S. EPA, 1996). Ozone is also phytotoxic, causing 

considerable damage to vegetation throughout the world. Some plant species are more sensitive to 

ozone than are humans (U.S. EPA, 1996). The primary National Ambient Air Quality Standard 

(NAAQS) for ozone is designed to protect human health, and the secondary NAAQS is set to 

achieve protection of the public welfare, including vegetation. The primary and secondary 

standards for ozone are the same. The new 8-hour, 0.08 ppm NAAQS for ozone is expected to be 

more protective of vegetation than the 1-hour, 0.12 ppm NAAQS.1

 Attaining and maintaining 

compliance with the NAAQS is the responsibility of states and EPA rather than the FLMs. FLAG 

guidelines are not for regulatory purposes, but provide guidance for the FLM to identify ozone 

impacts on lands they manage. 

FLAG recognizes that specific relationships between precursor emissions and ambient ozone 

concentrations at a FLM area are difficult to quantify. Further, it is difficult to quantify the specific 

relationship between ambient ozone at a FLM area and vegetation response. Therefore, FLAG has 

chosen to focus on the effects of ozone on vegetation and the levels of ozone generally known to be 

phytotoxic in FLM areas as indicators of concern regarding ozone impacts on AQRVs. 

The objectives of this chapter are to document information currently known about vegetation 

response to ozone exposure, and to describe FLM procedures for responding to new source review 

(NSR) permit applications. If the FLMs have evidence that ozone is adversely impacting an area 

they manage, they will work to restrict further emissions of ozone precursors until those adverse 

impacts are mitigated. 

b. Ozone Effects on Vegetation

Most ozone effects research has focused on agricultural crops because of the large economic losses 

that have been documented. Nevertheless, research has identified many native plants in natural 

ecosystems that are sensitive to ozone (U.S. EPA, 1996). Some of these ozone-sensitive plant species 

have been used as “bioindicators” of ozone to document phytotoxicity of ozone in the field due to 

ambient ozone. A listing of key literature describing known ozone effects on native vegetation is 

provided in Appendix H. 

The definitions for ozone injury and damage used by FLMs are based on the classical definitions (for 

example, see Guderian 1977). Injury is all physical or biological responses to pollutants, such as 

change in metabolism, reduced photosynthesis, leaf necrosis, premature leaf drop, and chlorosis. 

Damage is reduction in the intended use or value of the biological or physical resource; for example, 

 

1

The new 8-hour standard is currently being challenged in court and is not yet enforced; the 1-hour standard is still in 

effect. 
76 

economic production, ecological structure and function, aesthetic value, and biological or genetic 

diversity that may be altered through the impact of pollutants. 

Ozone enters plants through leaf stomata. It oxidizes plant tissue, causing changes in biochemical and 

physiological processes. These biochemical and physiological changes occur within the leaf long 

before visible necrotic symptoms appear (Guderian et al.1985). Plants must expend energy to detoxify 

ozone and repair injured tissue that could otherwise be used for growth or for maintenance of plant 

health. The injured plant cells eventually die if detoxification and repair cannot keep up with ozone 

uptake. The mesophyll cells under the upper epidermis of leaves are the most sensitive to ozone, and 

those are the first cells to die. The adjacent epidermal cells then die, forming a small black or brown 

interveinal necrotic lesion that becomes visible on the upper surface of the leaf. These visible lesions 

most frequently begin to develop on leaves that have just become fully matured, with older leaves on a 

stem showing increased amounts of injury. These lesions, termed oxidant stipple2

, are quite specific 

indicators that the plant has been exposed to ozone. Other plant symptoms that can result from 

exposure to ozone, with or without the presence of oxidant stipple, include chlorosis, premature 

senescence, and reduced growth. However, these symptoms are non-specific for ozone since other 

stressors can also cause them to occur. Further, these non-specific symptoms are difficult to quantify 

in natural ecosystems, although limited data are available from exposure response experiments to 

estimate growth losses from specific ozone exposures. In general, the only indicator that a FLM has to 

document that ozone has impacted vegetation is visible symptoms of injury such as oxidant stipple. 

In addition to affecting individual plants, ozone can also affect entire ecosystems. Research shows 

that plants growing in areas with high exposure to ambient ozone may undergo natural selection for 

ozone tolerance (U.S. EPA, 1996). The final result could be the elimination of the most ozonesensitive genotypes from the area. Regardless of the amount of ozone exposure, the magnitude of 

plant response may vary depending on the geographic area because of changes in meteorological and 

climatic conditions, and differences in plant conditions in space and time. Factors of most importance 

that influence plant response to ozone are the species/genotype, soil moisture, and nitrogen 

availability. Other factors influencing plant response to ozone include nutrient status, atmospheric 

humidity, temperature, solar radiation, phenological stage of development, day length, regional 

climatic differences, other pollutant interactions, and population/ecosystem interactions (U.S. EPA, 

1996). 

Ozone-induced physiological changes and/or growth reductions in plants may exist long before 

necrotic lesions appear on foliage; however, it is very difficult to attribute these effects directly to 

ozone. Similarly, changes in growth, ecosystem form or function, or biological or genetic diversity 

caused by ozone are difficult to document in natural ecosystems. Limited data are available regarding 

injury and growth response to specific ozone exposures. Given the difficulty in determining ozoneinduced physiological or growth changes in natural ecosystems, FLMs will utilize as indicators of 

ozone effects on vegetation (1) symptoms that are clearly ozone induced such as oxidant stipple, and 

(2) ozone exposures that have been shown to be phytotoxic. 

 

2

Specific symptoms of ozone injury in some plant species are different. A few species develop white or tan rather than 

brown or black lesions. This is termed “fleck” or “weather fleck” instead of oxidant stipple. In conifers, ozone causes 

banding of necrotic and green tissue near the tips of older needles, termed “chlorotic mottle.” 
77 

c. Recommended Metric to Determine Phytotoxic Ozone Concentrations 

Various metrics have been used to relate ozone exposure to plant response. Biologically relevant 

ozone metrics for plants cannot be directly related to, nor can they be calculated from, the 8-hour 

NAAQS for ozone. The NAAQS ozone metric does not directly account for peak concentrations, nor 

does it accumulate exposure, important parameters in any biologically relevant ozone metric. 

Biologically relevant metrics considered by FLAG include the W126, SUM06, AOT40, and ozone 

flux. The W126 is an index that uses a sigmoidal weighted function to weight each hourly ozone 

concentration. The W126 index is determined by summing all the sigmoidal weighted concentrations 

for a specified time period (Lefohn and Runeckles, 1987). The W126 index was described and used in 

EPA’s Air Quality Criteria for Ozone and Related Photochemical Oxidants, Vol. II (U.S. EPA, 1996) 

to characterize ozone trends. FLMs will use the W126 metric to determine phytotoxic ozone 

concentrations in FLM areas. The W126 is preferred to other cumulative metrics for a couple of 

reasons. First, the W126 preferentially weights the peak exposures, whereas other metrics, such as the 

AOT40 or the SUM06, do not. Second, the W126 accumulates ozone exposures at lower 

concentrations than does the AOT40 or SUM06. The AOT40 and SUM06 only accumulate 

concentrations above their particular threshold, e.g., 40 ppb for AOT40 and 60 ppb for SUM06. 

Phytotoxic effects have been shown to occur at exposure concentrations below 60 ppb (U.S. EPA 

1996). The AOT40 metric is commonly used in Europe. Some European scientists recently have 

concluded that the AOT40 metric is useful for exceedance mapping but not for assessment of biomass 

loss (Kaerenlampi and Skaerby 1996). Therefore, FLAG does not recommend the AOT40 for FLM 

assessments. 

The SUM06, W126, and AOT40 are ambient ozone exposure parameters, whereas flux is an ozone 

dose parameter for internal uptake. Flux is determined from ambient ozone concentration at the leaf 

surface and stomatal conductance. Ozone uptake relates more closely to plant response than does 

ambient ozone exposure. However, detoxification of ozone once it enters the plant is also an 

important component of plant response, and measuring uptake alone will not necessarily reflect the 

potential plant response. A benefit of flux is that it might allow differential weighting of daytime 

versus nighttime exposure (with daytime being weighted more heavily in most cases). Science has not 

advanced sufficiently for FLAG to recommend use of flux as a metric for plant response to ozone at 

this time. However, research on the use of flux as an ozone metric is continuing (Massman et al. 

2000) and it will be examined for possible future use. 

To use the W126 metric, the daily and seasonal time periods of measurement must also be determined. 

Although most ozone uptake occurs during the day, many plant species can have nighttime stomatal 

conductance resulting in ozone uptake (Musselman and Minnick 2000). Nighttime uptake is a 

function of many variables, including species, region (e.g., desert, deciduous forest, etc.), season, and 

elevation. In addition, many FLM areas, particularly those in mountainous regions, have high 

nighttime ozone exposures. Further, plants may be more sensitive to ozone at night (Musselman and 

Minnick 2000). Therefore, FLAG endorses use of a 24-hour time period for the W126 metric. 

 

Plant sensitivity and exposure to ozone will change throughout the growing season. Use of a rolling 

90-day cumulative value for the W126 metric would account for changes in exposure over the season. 

However, some vegetation exposure/response and ozone monitoring data are currently available using 

7-month (April through October) seasonal cumulative W126 values. In order to take advantage of this 

existing information, FLAG will use the April-October time period for the W126 metric. 
78 

FLAG recommends that peak concentrations (hourly ozone values greater than 100 ppb or N100) be 

included as a parameter of measurement in conjunction with the W126 parameter. Experimental 

evidence confirms that peak concentrations are important (U.S. EPA 1996). Accounting for peak 

concentrations also provides important information regarding the timing of events and helps determine 

if a response is due to chronic or acute exposure. Also, the quantitative exposure/growth response 

information used by FLAG for determination of critical exposure ozone levels was generated from 

experimentation based on fumigation treatments containing numerous occurrences of high hourly 

average concentrations. FLAG recognizes that oxidant stipple injury can occur at zero N100 for 

sensitive plant species; but the N100 should not be used alone as an indicator of sensitivity of 

vegetation to ozone. 

W126 and N100 values for injury and growth loss for selected eastern U.S. vegetation are presented in 

Table O-1 and Table O-2. Data for Table O-1 were derived under favorable environmental conditions, 

and report the lowest exposure level treatment where visible ozone symptoms were first observed. 

Thus, threshold exposure levels for ozone symptom response could be lower than those exposures 

reported here. Data from Table O-2 were calculated from exposure response relationships for a 10 

percent growth loss when plants are grown under favorable environmental conditions. It is recognized 

that data for other eastern U.S. plant species, and for plant species growing in the Western U.S., are 

not currently available. However, some additional exposure/response data for other species are 

available from which these values can be calculated. It is important to note that the critical level for 

injury or growth loss to vegetation from ozone is highly dependent on plant species and environmental 

conditions when the plants are exposed. The results obtained in Tables O-1 and O-2 could vary under 

different combinations of environmental conditions. Additional research under varying environmental 

conditions and ozone exposures should be conducted. 

Table O-1. W126 (ppm-h) and N100 (≥ 0.1 ppm) exposure levels that result in foliar necrotic 

symptoms for selected plant species (from Lefohn 1998.) 

Name W126 N100

Table mountain pine 20.0 2 

Sweetgum 5.6 3 

Sycamore 31.2 89 

Winged sumac 3.3 5 

Black cherry 11.5 10 

Tall milkweed 0.3 0 

Black-eyed Susan 12.8 50 

Dwarf dandelion 0.3 0 

Yellow buckeye 4.7 3 

Virginia pine 30.0 50 

Cutleaf coneflower 5.5 3 
79 

Table O-2. W126 (ppm-h) and N100 (≥ 0.1 ppm) exposure levels that resulted in a 10 percent 

growth loss for selected plant species (from Lefohn 1998.) 

Name W126 N100

Aspen 259 6.4 4 

Aspen wild 71.4 243 

Black Cherry 6.5 1 

Red Maple 85.4 245 

Whorled-wood aster 8.2 10 

Yellow poplar 14.4 4 

Eastern white pine 30.2 66 

Sugar maple 44.7 131 

Sycamore 15.4 27 

Winged sumac 9.7 4 

Ambient W126 and N100 values are available for many Class I areas in the eastern U.S., with values 

soon to be available for additional FLM areas. A table showing representative high and low W126 

and N100 values for selected FLM areas is appended to this report (Appendix 3.B). Unfortunately, 

ambient ozone data are lacking for many western U.S. FLM areas, and large differences in terrain and 

elevation may limit the use of nearby data. 

d. Identification of Ozone Sensitive AQRVs or Sensitive Receptors 

FLMs have determined that given the high ecological, aesthetic, and intrinsic value of federal lands, all 

native species are significant and warrant protection. Ideally, protection efforts would focus on the 

identification and protection of the most sensitive species in an area. Unfortunately, AQRV 

identification is limited by incomplete species inventories and/or lack of exposure/response data for 

most species of native vegetation. Sensitive species identification will improve as more information 

becomes available. In the meantime, FLAG is providing a preliminary list of sensitive plant species for 

each Class I area, i.e., those species that have been observed to exhibit ozone symptoms at ambient 

ozone exposures (Appendix 3.A). Those ambient levels have not necessarily occurred at the specific 

Class I area where the plants occur. AQRV lists will be available in the Air Synthesis and NRIS-AIR 

databases (See Section B.4.f. of this report) and will be updated as necessary. 

e. Review Process for Sources that Could Affect Ozone Levels or Vegetation in FLM Areas 

As mentioned above, NOx and VOC are ozone precursors. States and the EPA have based ozone 

control strategies in various parts of the country on the determination of which precursor is most likely 

to influence the formation of ozone. Information suggests that in areas where ozone formation is 

driven by VOC emissions, i.e., VOC-limited areas, VOC to NOx ratios are less than 4:1. In VOClimited areas, minimizing or reducing VOC emissions is the most effective means of limiting or 

lowering ozone concentrations. Conversely, in NOx-limited areas, where VOC to NOx ratios are 

greater than 15:1, controlling NOx emissions is most effective. It is generally thought that most rural 

areas of the U.S. are NOx-limited, most or all of the time, with the possible exception of the rural areas 

of southern California. The FLMs do not have current data to show that all areas are NOx limited, nor 

do they consider VOCs to be unimportant as ozone precursors. However, until there is enough 

information available for FLAG to determine whether ozone formation in each FLM area is primarily 

limited by NOx or VOC emissions, we will assume all FLM areas are NOx-limited and will focus on 
80 

control of NOx emissions. Where FLMs have information indicating a specific area is VOC limited, 

they will shift ozone protection strategy to focus on VOC rather than NOx emissions. 

Source/receptor modeling is required in most NSR permit applications for particulate matter, sulfur 

dioxide, and nitrogen dioxide. FLAG is aware of attempts by EPA and others to develop dispersion 

models that can relate emissions from a single source to changes in ozone concentrations. We 

recognize that there is currently no model available that can provide this kind of single source 

attribution information for ozone. Nevertheless, because of existing and suspected ozone concerns in 

a number of FLM areas (e.g., evidence of phytotoxic effects and high ambient concentrations), we will 

consider ozone effects when reviewing NSR permit applications. However, because single source 

attribution modeling is possible for both visibility and deposition, FLMs will be more concerned about 

ozone if modeling indicates NOx emissions are likely to cause an adverse impact on visibility, soils, 

and/or surface waters. 

The FLMs recognize that oxidant stipple can occur at hourly ozone concentrations that can be 

considered natural background levels (Singh et al. 1978). Many of the high hourly background 

concentrations can be attributed to stratospheric intrusions or stratospheric mixing in the upper 

troposphere (Singh et al. 1978); but stratospheric intrusions rarely occur in the middle and southern 

latitudes after May (Singh et al. 1980, Wooldridge et al. 1997), and thus do not coincide with the 

major portion of the growing season. However, oxidant stipple has been observed on foliage in the 

spring when these intrusions can occur. In general, oxidant stipple observed on foliage from June 

through September cannot be attributed to natural background ozone from stratospheric sources. Low 

levels of ambient ozone may occasionally occur in the troposphere from non-anthropogenic and nonstratospheric sources. 

The occurrence of oxidant stipple necrosis on plant foliage may indicate further ozone induced 

physiological and growth impacts. Point sources emit precursors that could produce ozone at the FLM 

area, and increased ozone could induce further injury or damage to vegetation. However, we assume 

that restriction on increases in ozone precursors will prevent additional ambient ozone and subsequent 

increases in injury or damage to vegetation in FLM managed areas. It is important that ambient ozone 

monitoring be conducted by the State or Local air pollution control agency or by the FLM to 

determine the seasonal ozone exposure. 

FLM actions or specific requests on a permit application will be based on the existing air pollution 

situation at the FLM area(s) that may be affected by the source. Some FLMs may rely on growth loss 

rather than foliar necrosis to make an adverse impact. Each FLM will determine if actions are 

warranted to limit emissions that might lead to increased ambient ozone, based on the expected impact 

of ozone in their particular area. 

FLM response will depend on whether or not: 

1. ozone vegetation effects have been documented in the area (as evidenced by foliar injury 

or damage to vegetation); 

2. ozone exposure levels occurring in the area are high enough that they could affect 

vegetation (i.e., ozone exposures are at levels shown to be phytotoxic). 

Figure O-1 outlines the general FLM process for responding to NSR permit applications based on 

ozone exposure and vegetation effects at the receptor site. Management decisions regarding 

acceptance of an existing or future ozone exposure will be area-specific and may differ 
81 

significantly between agencies, or even regionally within agencies. Each FLM will determine if 

injury and/or damage are necessary to warrant action, based on the expected impact in the area they 

manage. The decisions are based on the FLM interpretation of regulations, past experience in the 

NSR arena, availability of ozone effect exposure/response information for species that occur in the 

area, and other factors. The FLM will negotiate with the NSR permit applicant and the permitting 

authority regarding the options listed in Figure O-1. 

Figure O-1. FLM response to potential ozone effects from new emissions source.

 

 No 

 

 U Unknown Unknown Yes 

 

 

 Yes 

 No 

 

 

 Unknown Yes

 

 

 No 

 

Items referenced in Figure O-1: 

a. The FLM may recommend one or more of the following: 

- That the proposed source use stricter than BACT controls (e.g., Lowest Achievable Emission 

Rate [LAER]). 

- That the proposed source obtain NOx emission offsets that will benefit the potentially affected 

FLM area (as demonstrated by dispersion modeling). 

- That the permitting authority (i.e., state or EPA) conduct regional modeling to identify sources 

that are contributing significantly to ozone-associated impacts in the FLM area, and that the 

permitting authority then undertake actions necessary to reduce emissions from those sources (e.g., 

SIP revision). 

a

FLM not likely to 

object to permit; 

FLM may ask for d

FLM not likely 

to object to permit 

Ozone 

damage to 

vegetation

FLM not likely 

to object to 

permit; FLM 

may ask for 

c and/or d

a; FLM may ask for c

FLM not likely to 

object to permit; 

FLM may ask for c

START

Ozone 

damage to 

vegetation a

Ozone

exposure

currently

recognized as

phytotoxic; FLM

may ask for b
82 

b. The applicant calculate the ozone exposure for vegetation (using W126 and N100 metrics) for the 

affected FLM area(s) where such information is not already available. 

c. The permitting authority or applicant fund post-construction ambient ozone monitoring in or near 

the FLM area. 

d. The applicant conduct or fund post-construction ozone effects surveys in the FLM area and/or 

exposure/response effects research. 

Note: “Ozone exposure currently recognized as phytotoxic” is determined based on data from 

exposure response studies and ambient ozone at the site. The FLM may ask the applicant to 

calculate the ozone exposure values if these data are not already available. “Ozone damage to 

vegetation” is determined from field observations at the impacted site. 

f. Further Guidance to FLMs 

As mentioned above, limited information about ozone exposure/response relationships in plants and 

lack of an ozone source/receptor model make it difficult to protect FLM areas from the effects of 

ozone from new sources. However, there are other area-specific gaps in information that also limit 

protection efforts. It is important for local land managers to attempt to collect the missing 

information. This section provides guidance specifically to FLMs on what types of data should be 

collected and how the data could be collected. 

Identifying and Monitoring Ozone-sensitive AQRVs

Many FLM areas need more details regarding plant species presence, location, and abundance. FLAG 

recommends FLMs gather this information, where needed, and refine their lists of area-specific ozonesensitive plants. FLMs are currently developing lists of sensitive species to crosscheck with the plant 

species list for their area to determine potential sensitivity to ozone. In the future, the FLMs will place 

ozone sensitive plant species lists in the NRIS-AIR or Air Synthesis databases for comparison to plant 

species lists for each wilderness area or national park. 

FLAG recommends that once local FLMs have developed lists of potentially sensitive AQRVs 

specific for their site, they conduct surveys to detect the presence of ozone-induced foliar injury on the 

selected species. The USDA/FS Forest Health Monitoring (FHM) Program has developed foliar injury 

survey protocols and QA/QC procedures that can be used to collect this information. Another 

resource is the foliar injury training module developed by the NPS Air Resources Division and 

Pennsylvania State University. This module helps field staff identify and quantify ozone injury 

symptoms on plant foliage. Field crews must obtain proper training and field experience in identifying 

foliar injury symptoms before surveys can be conducted. 

 

Ideally, to verify ozone-induced foliar injury symptoms in the field, exposure/response fumigation 

studies should be conducted on these species, using concentrations that reflect current ambient 

exposure. Plants should also be tested at higher exposures, simulating increased levels of ambient 

ozone that might occur in the future. Due to the expense of constructing and operating such systems, it 

would be most appropriate for agencies to join resources and develop regional fumigation facilities. 

At a minimum, such facilities should be constructed both in the eastern and western U.S., since 

ambient conditions at an eastern facility might not be appropriate for western species and vice versa. 
83 

Ambient Ozone Monitoring

Many FLM areas do not currently have either on-site or nearby ambient ozone monitoring data. 

FLAG recommends that local FLMs make every effort to collect this information and that they use 

quality-assured ambient ozone monitoring protocols developed by the EPA and the state air quality 

agency. Continuous (active) monitoring is preferred since this type of data is necessary to determine 

compliance with the ozone NAAQS. Continuous monitoring is also necessary to determine the 

temporal dynamics of ozone exposure for vegetation, and is necessary to calculate the W126 and 

N100 parameters. Unfortunately, continuous monitoring is expensive and requires electric power that 

is often not available in or near remote FLM areas. When installing a continuous monitor is not an 

option, FLAG recommends use of passive monitors. Passive monitors give total exposure loading 

values (SUM00) for a specified period of time. The data are useful for indicating year-to-year changes 

in total ozone exposure at an individual site, and for indicating where continuous monitors should be 

installed. However, FLMs recognize the limitation of passive samplers in relating ozone exposure to 

plant response. 

g. Ozone Air Pollution Web Sites 

U.S. EPA ozone information: 

 http://www.epa.gov/airlinks 

 http://www.epa.gov gov/oar/oaqps/cleanair.html 

 http://www.epa.gov/naaqsfin/o3health.htm 

 http://www.epa.gov/acidrain/castnet 

NPS ozone information: 

 http://www2.nature.nps.gov/ard/gas/network.htm; 

 http://www2.nature.nps.gov/ard/veginj.htm 

Ozone effects research, USDA ARS, North Carolina: 

 http://www.ces.ncsu.edu/depts/pp/notes/Ozone/ozone.html 

Ozone effects research, England: 

 http://www.ncl.ac.uk/airweb/ozone/ozone.htm 

Ozone effects research, Switzerland: 

 http://www.wsl.ch/forest/risks/wsidb/projects/ozone/ozoneENG.html 

Ozone exposure metrics for vegetation: 

 http://www.asl-associates.com/ 

 Ozone W126 calculator: 

 http://216.48.37.155/calculator/index.htm 
84 

Appendix 3.A: A Preliminary Listing for Selected USDA/FS, NPS, and FWS Class I Areas of 

Plant Species that have been Shown to be Sensitive Receptors for Ozone. 

1. USDA/FS CLASS I WILDERNESS AREAS

Alabama

Sipsey 

Black Cherry Prunus serotina

Blackberry Rubus canadensis

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera

Arkansas

Upper Buffalo

Blackberry Rubus canadensis

Arizona

Chiricahua

Serviceberry Amelanchier alnifola

Chokecherry Prunus virginiana

 Globemallow Sphaeralcea 

 Ponderosa Pine Pinus ponderosa

Skunkbush Rhus trilobata

Galiuro

Serviceberry Amelanchier alnifola

Chokecherry Prunus virginiana

Globemallow Sphaeralcea 

 Ponderosa Pine Pinus ponderosa

Skunkbush Rhus trilobata

Mazatzal

Aspen Populus tremuloides

 Ponderosa Pine Pinus ponderosa

 Skunkbush Rhus trilobata

Mount Baldy

Arizona Willow Salix

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Pine Mountain

Aspen Populus tremuloides

 Ponderosa Pine Pinus ponderosa

Skunkbush Rhus trilobata

Sierra Ancha

Aspen Populus tremuloides

 Ponderosa Pine Pinus ponderosa

 Skunkbush Rhus trilobata

Superstition

Aspen Populus tremuloides

 Ponderosa Pine Pinus ponderosa

Skunkbush Rhus trilobata

Sycamore Canyon

Aspen Populus tremuloides

 Ponderosa Pine Pinus ponderosa

 Skunkbush Rhus trilobata 
85 

California

Agua Tibia

 Jeffrey Pine Pinus jeffreyi 

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola 

Ansel Adams

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Caribou

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta 

Cucamonga

Jeffrey Pine Pinus jeffreyi

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Desolation

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

Dome Land

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola 

Emmigrant

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Ponderosa Pine Pinus ponderosa 

Hoover

 Ponderosa Pine Pinus ponderosa 

John Muir

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Kaiser

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Marble Mountain

Jeffrey Pine Pinus jeffreyi 

Limber Pine Pinus flexilis

Lodgepole Pine Pinus contorta

Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Mokelumme

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola
86 

San Gorgonio

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

Western White Pine Pinus monticola 

San Jacinto

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola 

San Rafael

Jeffrey Pine Pinus jeffreyi

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

South Warner

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Thousand Lakes

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Yolla Bolly - Middle Eel

 Jeffrey Pine Pinus jeffreyi 

 Limber Pine Pinus flexilis

 Lodgepole Pine Pinus contorta

 Ponderosa Pine Pinus ponderosa

 Western White Pine Pinus monticola

Colorado

Eagles Nest

 Subalpine fir Abies lasiocarpa 

 White clover Trifolium repens

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

Flat Tops

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.
87 

Maroon Bells – Snowmass

 White fir Abies concolor

 Subalpine fir Abies lasiocarpa

 Sagebrush Artemesia sp.

 Trembling aspen Populus tremuloides

Mount Zirkel

 Subalpine fir Abies lasiocarpa 

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

Rawah

 White fir Abies concolor 

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

Weminuche

 White fir Abies concolor 

 Subalpine fir Abies lasiocarpa 

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Huckleberry Vaccinium sp.

West Elk

 White fir Abies concolor 

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Saskatoon serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp 

Hybrid poplar Populus deloides x trichocarpa

 Ninebark Pysocarpus sp. 

Chockcherry Prunus vierginiana

 Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

Florida

Bradwell Bay

Blackberry Rubus canadensis

Staghorn Sumac Rhus typhina

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera
88 

Georgia

Cohutta

Black Cherry Prunus serotina

Blackberry Rubus canadensis

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera

Idaho

Sawtooth

 Ponderosa Pine Pinus ponderosa

Minnesota

Boundary Waters Canoe Area

 Aspen Populus tremuloides

Chokecherry Prunus virginiana

 Eastern White Pine Pinus strobus

Missouri

Hercules-Glades

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana

Nevada

Jarbridge

 Ponderosa Pine Pinus ponderosa 

New Hampshire

Great Gulf 

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana

Presidential Range - Dry River

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Red Spruce Picea rubens

White Ash Fraxinus americana 

North Carolina

Joyce Kilmer - Slickrock

American Sycamore Platinus occidentalis

Black Cherry Prunus serotina

Blackberry Rubus canadensis

Elderberry Sambucus canadensis

 Flowering Dogwood Cornus florida

Pin Cherry Prunus pensylvanica

Poison Ivy Rhus radicans

Red Maple Acer rubrum

Red Oak Quercus rubra 

Sassafrass Sassafras albidum

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana

 Eastern White Pine Pinus strobus
89 

Linville Gorge

American Sycamore Platinus occidentalis

Black Cherry Prunus serotina

Blackberry Rubus canadensis

 Flowering Dogwood Cornus florida

Red Maple Acer rubrum

Red Oak Quercus rubra 

Sassafrass Sassafras albidum

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera

 Eastern White Pine Pinus strobus

Shining Rock 

Black Cherry Prunus serotina

Black-Eyed Susan Rudbeckia hirta

Blackberry Rubus canadensis

 Chokecherry Prunus virginiana

Flowering Dogwood Cornus florida

Milkweed Asclepias syriaca

Poison Ivy Rhus radicans

Red Oak Quercus rubra 

Sassafrass Sassafras albidum

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana

 Eastern White Pine Pinus strobus 

Oregon*

Diamond Peak

 Western Serviceberry Amelancier alnifolia 

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

Stink Currant Ribes bracteosum 

Eagle Cap

 Western Serviceberry Amelancier alnifolia 

 Ponderosa Pine Pinus ponderosa

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

Gearhart Mountain

 Western Serviceberry Amelancier alnifolia 

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 

*

Plant species listed for Oregon have been identified as ozone sensitive in laboratory fumigations. Ozone injury to 

some of these species has not been verified in the field. 
90 

Hells Canyon

 Western Serviceberry Amelancier alnifolia 

 Ponderosa Pine Pinus ponderosa

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

 Black Twin-berry Lonicera involucrata

 Mallow Ninebark Physocarpus malvaceus 

 Black Cottonwood Populus trichocarpa 

Kalmiopsis

 Western Serviceberry Amelancier alnifolia 

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

Mount Hood

 Western Serviceberry Amelancier alnifolia 

Pacific ninebark Physocarpus capitatus

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa

 Stink Currant Ribes bracteosum

Mount Jefferson

 Western Serviceberry Amelancier alnifolia 

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa

 Stink Currant Ribes bracteosum

Mount Washington

 Western Serviceberry Amelancier alnifolia 

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Stink Currant Ribes bracteosum 

Mountain Lakes

 Western Serviceberry Amelancier alnifolia 

Pacific ninebark Physocarpus capitatus

 Ponderosa Pine Pinus ponderosa

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa 
91 

Strawberry Mountain

 Western Serviceberry Amelancier alnifolia 

 Ponderosa Pine Pinus ponderosa

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata 

Three Sisters

 Western Serviceberry Amelancier alnifolia 

Pacific ninebark Physocarpus capitatus

 Ponderosa Pine Pinus ponderosa

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

Vermont

Lye Brook

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Red Spruce Picea rubens

White Ash Fraxinus americana

Virginia

James River Face

Black Cherry Prunus serotina

Blackberry Rubus canadensis

Chokecherry Prunus virginiana

 Flowering Dogwood Cornus florida

Milkweed Asclepias syriaca

Poison Ivy Rhus radicans

Red Oak Quercus rubra 

Sassafrass Sassafras albidum

Sweetgum Liquidambar styraciflua

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana

 Eastern White Pine Pinus strobus

Washington*

Alpine Lakes

 Western Serviceberry Amelancier alnifolia 

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Stink Currant Ribes bracteosum 

 

*

Plant species listed for Washington have been identified as ozone sensitive in laboratory fumigations. Ozone injury to 

some of these species has not been verified in the field. 
92 

Glacier Peak

 Western Serviceberry Amelancier alnifolia 

Pacific ninebark Physocarpus capitatus

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa

 Stink Currant Ribes bracteosum

Goat Rocks

 Western Serviceberry Amelancier alnifolia 

Pacific ninebark Physocarpus capitatus

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa

 Stink Currant Ribes bracteosum

Mount Adams

 Western Serviceberry Amelancier alnifolia

Pacific ninebark Physocarpus capitatus

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Red Alder Alnus rubra

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata

 Black Cottonwood Populus trichocarpa

 Stink Currant Ribes bracteosum

Paysayten

 Western Serviceberry Amelancier alnifolia 

 Quaking Aspen Populus tremuloides

Scouler Willow Salix scouleriana 

Thin-leaved Huckleberry Vaccinium membranaceum 

 Mountain Ash Sorbus sitchensis

 Black Twin-berry Lonicera involucrata 

West Virginia

Dolly Sods

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana 

Otter Creek

Black Cherry Prunus serotina

Elderberry Sambucus canadensis

Milkweed Asclepias syriaca

Red Spruce Picea rubens

Tulip Poplar Liriodendron tulipifera

White Ash Fraxinus americana
93 

Wisconsin

Rainbow Lake 

Aspen Populus tremuloides

Chokecherry Prunus virginiana

Eastern White Pine Pinus strobus

Wyoming

Bridger

 Ponderosa Pine Pinus ponderosa

Fitzpatrick (probable species) 

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp. 

Hybrid poplar Populus deloides x trichocarpa

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Ninebark Pysocarpus sp.

Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

North Absoroka (probable species) 

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp. 

Hybrid poplar Populus deloides x trichocarpa

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Ninebark Pysocarpus sp.

Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.

Teton

 Ponderosa Pine Pinus ponderosa

Washakie (probable species) 

 Subalpine fir Abies lasiocarpa 

 Boxelder Acer negundo 

 Serviceberry Amelanchier alnifolia

 Sagebrush Artemesia sp. 

Hybrid poplar Populus deloides x trichocarpa

Trembling aspen Populus tremuloides

 Chockcherry Prunus vierginiana

 Ninebark Pysocarpus sp.

Thimbleberry Rubus parviflorus 

 Squawberry Rhus trilobata 

 Huckleberry Vaccinium sp.
94 

2. NPS CLASS I AREAS 

Alaska

Denali NP

 Quaking aspen Populus tremuloides

 Black poplar Populus balsamifera 

Arizona

Chiricahua NM

 Arizona pine Pinus ponderosa

 Skunkbush Rhus trilobata

 White stem blazingstar Mentzelia albicaulis

 Black cherry Prunus serotina

 White clover Trifolium repens

Grand Canyon NP

 Cottonwood Populus fremontii

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Single-leaf ash Fraxinus anomala

 Skunkbush Rhus trilobata

 Serviceberry Amelanchier alnifolia

 White stem blazingstar Mentzelia albicaulis

 Smooth desert dandelion Malacothrix glabrata

 Desert dandelion Malacothrix glabrata

 White clover Trifolium repens

Petrified Forest NP

 Skunkbush Rhus trilobata

 Cheat grass Bromus tectorum

 Red-stem stork’s bill Erodium cicutarium

 Perrenial rye grass Lolium perenne

 White stem blazingstar Mentzelia albicaulis

Saguaro NP

 Ponderosa pine Pinus ponderosa

 Skunkbush Rhus trilobata

 Quaking aspen Populus tremuloides 

California

Joshua Tree NP

Single-leaf ash Fraxinus anomala

 Skunkbush Rhus trilobata

 White stem blazingstar Mentzelia albicaulis

Kings Canyon NP

Jeffrey pine Pinus jeffreyi

 Ponderosa pine Pinus ponderosa

 Twinberry Lonicera involucrata

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 Skunkbush Rhus trilobata

 Butterweed groundsel Senecio serra 

 White clover Trifolium repens

 Black poplar Populus balsamifera trichocarpa

Lassen Volcanic NP

Skunkbush Rhus trilobata

 Chokecherry Prunus virginiana

 Ponderosa pine Pinus ponderosa

 White clover Trifolium repens

 Jeffrey pine Pinus jeffreyi
95 

Lava Beds NM

Chokecherry Prunus virginiana

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Jeffrey pine Pinus jeffreyi

Point Reyes National Seashore

 Ledebour’s honeysuckle Lonicera involucrata

 White clover Trifolium repens

Redwood NP

 White clover Trifolium repens

 Black poplar Populus balsamifera trichocarpa

 Chokecherry Prunus virginiana

 Jeffrey pine Pinus jeffreyi

Sequoia NP

 Jeffrey pine Pinus jeffreyi

 Ponderosa pine Pinus ponderosa

 Twinberry Lonicera involucrata

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 Skunkbush Rhus trilobata

 Butterweed groundsel Senecio serra 

 White clover Trifolium repens

 Black poplar Populus balsamifera trichocarpa

Yosemite NP

Ponderosa pine Pinus ponderosa

 White clover Trifolium repens

 Skunkbush Rhus trilobata

 Twinberry honeysuckle Lonicera involucrata

 Chokecherry Prunus virginiana

Colorado

Black Canyon of the Gunnison NP

 Serviceberry Amelanchier alnifolia

 Quaking aspen Populus tremuloides

 Skunkbush Rhus trilobata 

 White clover Trifolium repens

 Chokecherry Prunus virginiana

Great Sand Dunes NM

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Serviceberry Amelanchier alnifolia

 Mountain ninebark Physocarpus monogynus

 Skunkbush Rhus trilobata

 White stem blazingstar Mentzelia albicaulis

 White clover Trifolium repens 

Mesa Verde NP

Ponderosa pine Pinus ponderosa

Spreading dogbane Apocynum androsaemifolium

Box elder Acer negundo

Cheat grass Bromus tectorum

Poison ivy Toxicodendron radicans

Skunkbush Rhus trilobata

 Serviceberry Amelanchier alnifolia

 Quaking aspen Populus tremuloides

 White stem blazingstar Mentzelia albicaulis

 White clover Trifolium repens
96 

Rocky Mountain NP

 Wild strawberry Fragaria virginiana

 Mountain ninebark Physocarpus monogyna

 Ponderosa pine Pinus ponderosa

 Balsam poplar Populus balsamifera

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 White clover Trifolium repens

Hawaii

Haleakala NP

Ponderosa pine Pinus ponderosa

 White clover Trifolium repens

Hawaii Volcanoes NP

 White clover Trifolium repens

Idaho

Craters of the Moon NM

 Black poplar Populus balsamifera trichocarpa

 Quaking aspen Populus tremuloides

Kentucky

Mammoth Cave NP

 Yellow-poplar Liriodendron tulipifera

 Red maple Acer rubrum

 Poke milkweed Asclepias exaltata

 American sycamore Platanus occidentalis

 Black cherry Prunus serotina

 Black-eyed susan Rudbeckia hirta

 Cutleaf coneflower Rudbeckia laciniata

 Sassafras Sassafras albidum

 Green ash Fraxinus pennsylvanica

 White clover Trifolium repens

Maine

Acadia NP

Broad-leaf aster Aster macrophyllus

 Black cherry Prunus serotina

 Quaking aspen Populus tremuloides

 White ash Fraxinus americana

 Spreading dogbane Apocynum androsaemiolium

Michigan

Isle Royale NP

 Common snowberry Symphoricarpos albus

 Quaking aspen Populus tremuloides

 Twinberry honeysuckle Lonicera involucrata

 Black poplar Populus balsamifera

 White clover Trifolium repens

 Red maple Acer rubrum

 Chokecherry Prunus virginiana

 Bigleaf aster Aster macrophyllus

 Paper birch Betula papyrifera
97 

Minnesota

Voyageurs NP

Green ash Fraxinus pennsylvanica

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 White clover Trifolium repens

 Snowberry Symphoricarpos albus

 Paper birch Betula papyrifera

 Common milkweed Asclepias syriaca

 Black poplar Populus balsamifera

 Red maple Acer rubrum

Montana

Glacier NP

Paper birch Betula papyrifera

 Wild strawberry Fragaria virginiana

 Twinberry Lonicera involucrata

 Rock-spiraea Holodiscus discolor

 Ponderosa pine Pinus ponderosa

 Black poplar Populus balsamifera trichocarpa

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 Snowberry Symphoricarpos albus

 White clover Trifolium repens

New Mexico

Bandelier NM

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Skunkbush Rhus trilobata

 White clover Trifolium repens

Carlsbad Caverns NP

 Ponderosa pine Pinus ponderosa

 Fremont’s cottonwood Populus fremontii

 Quaking aspen Populus tremuloides

 White stem blazingstar Mentzelia albicaulis

 Black cherry Prunus serotina

North Carolina/Tennessee

Great Smoky Mountains NP 

 Yellow-poplar Liriodendron tulipifera

 Red maple Acer rubrum

 Tall milkweed Asclepias exaltata

 Table-mountain pine Pinus pungens

 American sycamore Platanus occidentalis

 Black cherry Prunus serotina

 Winged sumac Rhus copallina

 Black-eyed susan Rudbeckia hirta

 Cutleaf coneflower Rudbeckia laciniata

 Crown-beard Verbesina occidentalis

 Sassafras Sassafras albidum
98 

North Dakota

Theodore Roosevelt NP

 Paper birch Betula papyrifera

 Wild strawberry Fragaria virginiana

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 White clover Trifolium repens

Oregon

Crater Lake NP

Ponderosa pine Pinus ponderosa

 Black poplar Populus balsamifera trichocarpa 

 Quaking aspen Populus tremuloides 

 Lodgepole pine Pinus contorta 

South Dakota

Badlands NP

Green ash Fraxinus pennsylvanica

 Ponderosa pine Pinus ponderosa

 Chokecherry Prunus virginiana

 Snowberry Symphoricarpos albus

 Western wormwood Artemisia ludoviciana 

Wind Cave NP

 Wild strawberry Fragaria virginiana

 Green ash Fraxinus pennsylvanica

 Quaking aspen Populus tremuloides

 Ponderosa pine Pinus ponderosa

 Chokecherry Prunus virginiana

Texas

Big Bend NP

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides 

 Black cherry Prunus serotina

 Skunkbush Rhus trilobata

Guadalupe Mountains NP

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Black cherry Prunus serotina

 White stem blazingstar Mentzelia albicaulis

 Chokecherry Prunus virginiana

Utah

Arches NP

Cottonwood Populus fremontii

 Single-leaf ash Fraxinus anomala

 Skunkbush Rhus trilobata

 White stem blazingstar Mentzelia albicaulis

Bryce Canyon NP

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Skunkbush Rhus trilobata

 White clover Trifolium repens
99 

Canyonlands NP

 Cottonwood Populus fremontii

 Single-leaf ash Fraxinus anomala

 Serviceberry Amelanchier alnifolia

 Quaking aspen Populus tremuloides

 White stem blazingstar Mentzelia albicaulis

Capitol Reef NP

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Cottonwood Populus fremontii

 Single-leaf ash Fraxinus anomala

 Serviceberry Amelanchier alnifolia

 Skunkbush Rhus trilobata

 White stem blazingstar Mentzelia albicaulis

 White clover Trifolium repens

 Smooth desert dandelion Malacothrix glabrata

Zion NP

 Cottonwood Populus fremontii

 Ponderosa pine Pinus ponderosa

 Quaking aspen Populus tremuloides

 Skunkbush Rhus trilobata

 Serviceberry Amelanchier alnifolia

 White stem blazingstar Mentzelia albicaulis

 White clover Trifolium repens

Virginia

Shenandoah NP

 Black cherry Prunus serotina

 Quaking aspen Populus tremuloides

 White ash Fraxinus americana

 Common milkweed Asclepias syriaca 

 Yellow-poplar Liriodendron tulipifera

 American sycamore Platanus occidentalis

 White clover Trifolium repens

Washington

Mount Rainier NP

Ponderosa pine Pinus ponderosa

 Black poplar Populus balsamifera trichocarpa 

 Quaking aspen Populus tremuloides 

Twinberry Lonicera involucrata 

Serviceberry Amelanchier alnifolia 

Snowberry Symphoricarpos albus 

North Cascades NP

Ponderosa pine Pinus ponderosa

 Black poplar Populus balsamifera trichocarpa

 Paper birch Betula papyrifera 

 Box elder Acer negundo 

Twinberry Lonicera involucrata 

Serviceberry Amelanchier alnifolia 

Snowberry Symphoricarpos albus

Olympic NP

Black poplar Populus balsamifera trichocarpa 

 Twinberry Lonicera involucrata 

Serviceberry Amelanchier alnifolia 

Snowberry Symphoricarpos albus 
100 

Wyoming

Grand Teton NP

 Wild strawberry Fragaria virginiana

 Twinberry Lonicera involucrata

 Black poplar Populus balsamifera trichocarpa 

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 Skunkbush Rhus trilobata

 Bitterweed groundsel Senecio serra

 White clover Trifolium repens

Yellowstone NP

 Wild strawberry Fragaria virginiana

 Twinberry Lonicera involucrata

 White stem blazingstar Mentzelia albicaulis

 Black poplar Populus balsamifera trichocarpa

 Quaking aspen Populus tremuloides

 Chokecherry Prunus virginiana

 Skunkbush Rhus trilobata

 Butterweed groundsel Senecio serra 

 White clover Trifolium repens
101 

3. FWS CLASS I WILDERNESS AREAS

Florida

Chassahowitzka

Eastern redbud Cercis canadensis 

 Sweetgum Liquidambar styraciflua

 Loblolly pine Pinus taeda

 Black cherry Prunus serotina

 Dwarf sumac Rhus copallina

 Blackeyed Susan Rudbeckia hirta

Georgia

Okefenokee 

 American sycamore Platanus occidentalis 

 Black cherry Prunus serotina 

 Dwarf sumac Rhus copallina 

 Eastern poison ivy Toxicodendron radicans 

 Eastern redbud Cercis canadensis 

 Flowering dogwood Cornus florida 

 Loblolly pine Pinus taeda 

 Red maple Acer rubrum 

 Sweetgum Liquidambar styraciflua 

 Tree-of-heaven Ailanthus altissima 

 Virginia creeper Parthenocissus quinquefolia 

Maine

Moosehorn

Spreading dogbane Apocynum androsaemifolium 

 Swamp milkweed Asclepias incarnata 

 Whorled wood aster Aster acuminatus 

 Bigleaf aster Aster macrophyllus

 Parasol aster Aster umbellatus 

 White ash Fraxinus americana 

 Green ash Fraxinus pennsylvanica 

 Quaking aspen Populus tremuloides 

 Pin cherry Prunus pennsylvanica

 Black cherry Prunus serotina 

Common chokecherry Prunus virginiana

 Staghorn sumac Rhus typhina

 Allegheny blackberry Rubus allegheniensis

 American elder Sambucus canadensis

Michigan

Seney 

 American basswood Tilia americana 

 Bigleaf aster Aster macrophyllus 

 Blackeyed Susan Rudbeckia hirta 

 Common milkweed Asclepias syriaca 

 Eastern poison ivy Toxicodendron radicans 

 Quaking aspen Populus tremuloides 

 Red maple Acer rubrum 

 Sambucus nigra Sambucus canadensis 

 Scarlet elderberry Sambucus racemosa 

 Spreading dogbane Apocynum androsaemifolium 
102 

Missouri

Mingo

Tuliptree Liriodendendron tulipifera 

 Virginia creeper Parthenocissus quinquefolia

Montana

Medicine Lake 

 Cheatgrass Bromus tectorum 

 Quaking aspen Populus tremuloides 

White ash Fraxinus americana 

New Jersey

Brigantine

 Boxelder Acer negundo 

 Tree-of-heaven Ailanthus altissima 

 Common milkweed Asclepias syriaca 

 Cheatgrass Bromus tectorum 

 Sweet gum Liquidambar styraciflua 

 Virginia creeper Parthenocissus quinquefolia 

 Pitch pine Pinus rigida 

Black cherry Prunus serotina 

 Winged sumac Rhus copallina 

 American elder Sambucus canadensis 

 Sassafras Sassafras albidum 

Common lilac Syringa vulgaris 

Poison-ivy Toxicodendron radicans 

Grape Vitis spp. 

North Dakota

Lostwood 

 Boxelder Acer negundo 

 Quaking aspen Populus tremuloides 

 Raspberry Rubus idaeus 

 Saskatoon serviceberry Amelanchier alnifolia 

Oklahoma

Wichita Mountains 

 Blackeyed Susan Rudbeckia hirta

 Cheatgrass Bromus tectorum 

 Eastern redbud Cercis canadensis 

 Green ash Fraxinus pennsylvanica 

 Smooth sumac Rhus glabra 

 Sugar Maple Acer saccharum 

 Virginia creeper Parthenocissus quinquefolia

South Carolina

Cape Romain

Sweetgum Liquidambar styraciflua

 Virginia creeper Parthenocissus quinquefolia 

Winged sumac Rhus copallina 

 American elder Sambucus canadensis 

 Chinese tallow tree Sapium sabiferum 

 Poison-ivy Toxicodendron radicans 

 Labrusca grape Vitis labrusca
103 

Appendix 3.B. List of Representative Low and High W126 and N100 Values 

for SELECTED NPS and FWS Areas.

SITE = ACADIA NATIONAL PARK

AIRS SITE NUMBER = 23-009-0101 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

ACAD 1988 43925 89 4485 5136 87.3 

ACAD 1996 10052 4 5085 5136 99.0 

______________________________________________________________________________________ 

SITE = ARCHES NATIONAL PARK

AIRS SITE NUMBER = 49-019-0101 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

ARCH 1989 21199 0 4260 5136 82.9 

ARCH 1990 1713 0 4639 5136 90.3 

______________________________________________________________________________________ 

SITE = BADLANDS NATIONAL PARK

AIRS SITE NUMBER = 46-071-1001 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

BADL 1988 13332 0 4791 5136 93.3 

BADL 1990 4766 0 4783 5136 93.1 

______________________________________________________________________________________ 
104 

SITE = BANDELIER NATIONAL MONUMENT

AIRS SITE NUMBER = 35-028-1002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

BAND 1991 44945 0 4997 5136 97.3 

BAND 1993 21854 0 4566 5136 88.9 

_____________________________________________________________________________________ 

SITE = BIG BEND NATIONAL PARK 

AIRS SITE NUMBER = 48-043-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

BIBE 1992 12169 0 4366 5136 85.0 

BIBE 1994 26667 0 4702 5136 91.5 

______________________________________________________________________________________ 

SITE = BIG THICKET NATIONAL PRESERVE

AIRS SITE NUMBER = 48-457-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

BITH 1987 21554 16 4401 5136 85.7 

BITH 1991 6763 1 3383 5136 65.9 

______________________________________________________________________________________ 

SITE = BRIGANTINE WILDERNESS AREA

AIRS SITE NUMBER = 34-001-0005 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

BRIG 1991 67729 109 4963 5136 96.6 

BRIG 1994 24901 2 4980 5136 97.0 

______________________________________________________________________________________ 
105 

SITE = CANYONLANDS NATIONAL PARK

AIRS SITE NUMBER = 49-037-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CANY 1993 21278 0 4390 5136 85.5 

CANY 1996 49676 0 4373 5136 85.1 

______________________________________________________________________________________ 

SITE = CAPE COD NATIONAL SEASHORE

AIRS SITE NUMBER = 25-001-0002 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CACO 1988 70427 174 4856 5136 94.5 

CACO 1993 23439 10 4675 5136 91.0 

______________________________________________________________________________________ 

SITE = CAPE ROMAIN WILDERNESS AREA

AIRS SITE NUMBER = 45-019-0046 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CARO 1991 4377 0 4943 5136 96.2 

CARO 1993 19019 0 4945 5136 96.3 

 ______________________________________________________________________________________ 

SITE = CHAMIZAL NATIONAL MEMORIAL

AIRS SITE NUMBER = 48-141-0044 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CHAM 1993 5310 1 4549 5136 88.6 

CHAM 1995 19564 14 4890 5136 95.2 

______________________________________________________________________________________ 
106 

SITE = CHANNEL ISLANDS NATIONAL PARK

AIRS SITE NUMBER = 06-111-0006 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CHIS 1991 14943 0 3268 5136 63.6 

CHIS 1992 33809 6 4549 5136 88.6 

______________________________________________________________________________________ 

SITE = CHIRICAHUA NATIONAL MONUMENT

AIRS SITE NUMBER = 04-003-8001 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CHIR 1992 20023 0 4521 5136 88.0 

CHIR 1994 36119 0 5005 5136 97.4 

______________________________________________________________________________________ 

SITE = COLORADO NATIONAL MONUMENT

AIRS SITE NUMBER = 08-077-0600 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

COLM 1987 35812 0 4418 5136 86.0 

COLM 1990 12229 0 5012 5136 97.6 

______________________________________________________________________________________ 

SITE = CONGAREE SWAMP NATIONAL MONUMENT

AIRS SITE NUMBER = 45-079-1006 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

COSW 1990 25577 14 4004 5136 78.0 

COSW 1994 5329 0 4221 5136 82.2 

______________________________________________________________________________________ 
107 

SITE = COWPENS NATIONAL BATTLEFIELD

AIRS SITE NUMBER = 45-021-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

COWP 1988 58732 69 4135 5136 80.5 

COWP 1990 22474 0 4784 5136 93.1 

______________________________________________________________________________________ 

SITE = CRATERS OF THE MOON NATIONAL MONUMENT

AIRS SITE NUMBER = 16-023-0101 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CRMO 1993 8563 0 4506 5136 87.7 

CRMO 1994 25462 0 4752 5136 92.5 

______________________________________________________________________________________ 

SITE = CUYAHOGA VALLEY NATIONAL RECREATION AREA 

AIRS SITE NUMBER = 39-153-2004 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

CUVA 1990 15249 15 3267 5136 63.6 

CUVA 1991 39670 33 4193 5136 81.6 

______________________________________________________________________________________ 

SITE = DEATH VALLEY NATIONAL PARK

AIRS SITE NUMBER = 06-027-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

DEVA 1994 68630 1 4125 5136 80.3 

DEVA 1996 46223 0 4380 5136 85.3 

______________________________________________________________________________________ 
108 

SITE = DENALI NATIONAL PARK 

AIRS SITE NUMBER = 02-290-0003 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

DENA 1993 2590 0 4773 5136 92.9 

DENA 1996 4144 0 4831 5136 94.1 

______________________________________________________________________________________ 

SITE = EVERGLADES NATIONAL PARK 

AIRS SITE NUMBER = 12-025-0030 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

EVER 1987 7968 0 3693 5136 71.9 

EVER 1991 1568 0 4202 5136 81.8 

 ______________________________________________________________________________________ 

SITE = GLACIER NATIONAL PARK

AIRS SITE NUMBER = 30-029-8001 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GLAC 1989 5871 0 5136 5136 100.0 

GLAC 1993 2314 0 5136 5136 100.0 

______________________________________________________________________________________ 

SITE = GREAT BASIN NATIONAL PARK

AIRS SITE NUMBER = 32-033-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GRBA 1995 22881 0 4836 5136 94.2 

GRBA 1996 38342 0 4800 5136 93.5 

______________________________________________________________________________________ 
109 

SITE = GRAND CANYON NATIONAL PARK

AIRS SITE NUMBER = 04-005-2003 AND 04-005-8001 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GRCA 1990 15430 0 3827 5136 74.5 

GRCA 1996 47476 0 4633 5136 90.2 

 ______________________________________________________________________________________ 

SITE = GREAT SAND DUNES NATIONAL MONUMENT

AIRS SITE NUMBER = 08-003-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GRSA 1989 10777 0 4436 5136 86.4 

GRSA 1991 16966 0 4130 5136 80.4 

______________________________________________________________________________________ 

SITE = GREAT SMOKY MTS NATIONAL PARK - CADES COVE SITE

AIRS SITE NUMBER = 47-009-0102 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GSCC 1994 14879 5 3988 5136 77.6 

GSCC 1996 24268 0 4805 5136 93.6 

______________________________________________________________________________________ 

SITE = GREAT SMOKY MTS NATIONAL PARK - CLINGMANS DOME SITE

AIRS SITE NUMBER = 47-155-0102 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GSCD 1993 40757 0 4087 5136 79.6 

GSCD 1996 74162 3 4104 5136 79.9 

______________________________________________________________________________________ 
110 

SITE = GREAT SMOKY MTS NATIONAL PARK - COVE MT SITE

AIRS SITE NUMBER = 47-155-0101 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GSCM 1992 49135 3 4620 5136 90.0 

GSCM 1996 98657 8 4879 5136 95.0 

______________________________________________________________________________________ 

SITE = GREAT SMOKY MTS NATIONAL PARK - LOOK ROCK SITE

AIRS SITE NUMBER = 47-009-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GSLR 1991 36430 0 4504 5136 87.7 

GSLR 1996 76608 5 4650 5136 90.5 

______________________________________________________________________________________ 

SITE = GUADALUPE MOUNTAINS NATIONAL PARK

AIRS SITE NUMBER = 48-109-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

GUMO 1990 13795 0 4531 5136 88.2 

GUMO 1992 25368 0 4120 5136 80.2 

______________________________________________________________________________________ 

SITE = HALEAKALA NATIONAL PARK

AIRS SITE NUMBER = 15-009-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

HALE 1992 609 0 4842 5136 94.3 

HALE 1993 1197 0 4668 5136 90.9 

 ______________________________________________________________________________________ 
111 

SITE = HAWAII VOLCANOES NATIONAL PARK

AIRS SITE NUMBER = 15-001-0005 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

HAVO 1987 3176 0 4068 5136 79.2 

HAVO 1991 244 0 4775 5136 93.0 

______________________________________________________________________________________ 

SITE = INDIANA DUNES NATIONAL LAKESHORE

AIRS SITE NUMBER = 18-127-0020 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

INDU 1989 11619 0 3708 5136 72.2 

INDU 1990 64667 66 3944 5136 76.8 

______________________________________________________________________________________ 

SITE = ISLE ROYALE NATIONAL PARK 

AIRS SITE NUMBER = 26-061-0101 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

ISRO 1988 11169 0 2341 5136 45.6 

ISRO 1991 6804 0 2631 5136 51.2 

______________________________________________________________________________________ 

SITE = JOSHUA TREE NATIONAL PARK

AIRS SITE NUMBER = 06-065-9002 AND 06-071-9002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

JOTR 1990 57422 32 3310 5136 64.4 

JOTR 1994 151025 224 4839 5136 94.2 

______________________________________________________________________________________ 
112 

SITE = LASSEN VOLCANIC NATIONAL PARK

AIRS SITE NUMBER = 06-089-3003 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

LAVO 1993 11637 0 4586 5136 89.3 

LAVO 1994 38104 0 4845 5136 94.3 

______________________________________________________________________________________ 

SITE = MAMMOTH CAVE NATIONAL PARK

AIRS SITE NUMBER = 21-061-0500 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

MACA 1988 51761 74 4828 5136 94.0 

MACA 1993 15306 1 4494 5136 87.5 

______________________________________________________________________________________ 

SITE = MESA VERDE NATIONAL PARK

AIRS SITE NUMBER = 08-083-0101 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

MEVE 1994 20007 0 4832 5136 94.1 

MEVE 1996 29698 0 4860 5136 94.6 

______________________________________________________________________________________ 

SITE = MOUNT RAINIER NATIONAL PARK

AIRS SITE NUMBER = 53-053-1010 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

MORA 1993 2845 0 4565 5136 88.9 

MORA 1994 6900 1 4224 5136 82.2 

______________________________________________________________________________________ 
113 

SITE = NORTH CASCADES NATIONAL PARK

AIRS SITE NUMBER = 53-057-0013 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

NOCA 1996 2173 0 4198 5136 81.7 

______________________________________________________________________________________ 

SITE = OLYMPIC NATIONAL PARK

AIRS SITE NUMBER = 53-009-0012 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

OLYM 1993 712 0 4585 5136 89.3 

OLYM 1995 1858 0 4667 5136 90.9 

______________________________________________________________________________________ 

SITE = PETRIFIED FOREST NATIONAL PARK

AIRS SITE NUMBER = 04-001-0012 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

PEFO 1988 14446 1 4830 5136 94.0 

PEFO 1989 25791 1 4696 5136 91.4 

______________________________________________________________________________________ 

SITE = PINNACLES NATIONAL MONUMENT

AIRS SITE NUMBER = 06-069-0003 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

PINN 1987 78874 86 4737 5136 92.2 

PINN 1994 32951 0 4771 5136 92.9 

______________________________________________________________________________________ 
114 

SITE = POINT REYES NATIONAL SEASHORE

AIRS SITE NUMBER = 06-041-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

PORE 1989 4813 0 4577 5136 89.1 

PORE 1990 1784 0 4856 5136 94.5 

______________________________________________________________________________________ 

SITE = REDWOOD NATIONAL PARK

AIRS SITE NUMBER = 06-015-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

REDW 1988 1814 0 4825 5136 93.9 

REDW 1989 1015 0 4624 5136 90.0 

______________________________________________________________________________________ 

SITE = ROCKY MOUNTAIN NATIONAL PARK 

AIRS SITE NUMBER = 08-069-0007 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

ROMO 1990 5592 0 4091 5136 79.7 

ROMO 1996 37033 0 4810 5136 93.7 

______________________________________________________________________________________ 

SITE = SAGUARO NATIONAL PARK

AIRS SITE NUMBER = 04-019-0021 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SAGU 1987 9184 0 3970 5136 77.3 

SAGU 1993 46792 1 4761 5136 92.7 

______________________________________________________________________________________ 
115 

SITE = SANTA MONICA MTNS NATIONAL RECREATION AREA 

AIRS SITE NUMBER = 06-037-1902 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SAMO 1989 73919 238 4770 5136 92.9 

SAMO 1991 63864 145 4700 5136 91.5 

______________________________________________________________________________________ 

SITE = SEQUOIA/KINGS CANYON NATIONAL PARKS - ASH MOUNTAIN

AIRS SITE NUMBER = 06-107-0005 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SEAM 1987 165538 245 4786 5136 93.2 

SEAM 1995 97343 73 4812 5136 93.7 

______________________________________________________________________________________ 

SITE = SEQUOIA/KINGS CANYON NATIONAL PARKS - GRANT GROVE 

AIRS SITE NUMBER = 06-107-0007 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SEGG 1994 135176 163 4814 5136 93.7 

SEGG 1995 80484 32 4264 5136 83.0 

______________________________________________________________________________________ 

SITE = SEQUOIA/KINGS CANYON NATIONAL PARKS - LOWER KAWEAH

AIRS SITE NUMBER = 06-107-0006 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SELK 1993 130157 137 4847 5136 94.4 

SELK 1995 71759 34 4786 5136 93.2 

______________________________________________________________________________________ 
116 

SITE = SHENANDOAH NATIONAL PARK - BIG MEADOWS

AIRS SITE NUMBER = 51-113-0003 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SVBM 1988 81013 63 4448 5136 86.6 

SVBM 1989 29297 0 4499 5136 87.6 

______________________________________________________________________________________ 

SITE = SHENANDOAH NATIONAL PARK - DICKEY RIDGE

AIRS SITE NUMBER = 51-187-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SVDR 1988 99239 160 3784 5136 73.7 

SVDR 1992 26841 0 4351 5136 84.7 

______________________________________________________________________________________ 

SITE = SHENANDOAH NATIONAL PARK - SAWMILL RUN

AIRS SITE NUMBER = 51-015-0042 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

SVSR 1988 56538 47 4722 5136 91.9 

SVSR 1989 16943 0 4490 5136 87.4 

______________________________________________________________________________________ 

SITE = THEODORE ROOSEVELT NATIONAL PARK - NORTH UNIT

AIRS SITE NUMBER = 38-053-0002 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

TRNO 1989 14184 0 4206 5136 81.9 

TRNO 1993 4573 0 4281 5136 83.4 

______________________________________________________________________________________ 
117 

SITE = VOYAGEURS NATIONAL PARK

AIRS SITE NUMBER = 27-071-0101 AND 27-137-0034 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

VOYA 1988 10026 3 4643 5136 90.4 

VOYA 1990 2234 0 4658 5136 90.7 

______________________________________________________________________________________ 

SITE = YELLOWSTONE NATIONAL PARK

AIRS SITE NUMBER = 56-039-1010 AND 56-039-1011 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

YELL 1990 3794 0 4663 5136 90.8 

YELL 1994 15212 0 4825 5136 93.9 

______________________________________________________________________________________ 

SITE = YOSEMITE NATIONAL PARK - CAMP MATHER

AIRS SITE NUMBER = 06-109-0004 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

YOCM 1989 21184 0 4321 5136 84.1 

YOCM 1994 52334 0 4567 5136 88.9 

______________________________________________________________________________________ 

SITE = YOSEMITE NATIONAL PARK - TURTLEBACK DOME

AIRS SITE NUMBER = 06-043-0003 

 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

YOTD 1994 103128 21 4881 5136 95.0 

YOTD 1995 65291 10 4467 5136 87.0 

______________________________________________________________________________________ 
118 

SITE = YOSEMITE NATIONAL PARK - WAWONA VALLEY 

AIRS SITE NUMBER = 06-043-0004 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

YOWV 1987 70513 44 4742 5136 92.3 

YOWV 1994 27911 0 4720 5136 91.9 

______________________________________________________________________________________ 

SITE = YOSEMITE NATIONAL PARK - YOSEMITE VALLEY

AIRS SITE NUMBER = 06-043-0005 

 APR-OCT 

 CUMULATIVE APR-OCT APR-OCT TOTAL PERCENT 

 W126 NO. OF HOURS NO. OF NO. OF DATA 

 EXPOSURE WITH OZONE VALID HOURS HOURS IN CAPTURE FOR 

PARK YEAR PPB-HRS >=100PPB OF OZONE APR-OCT APR-OCT 

YOYV 1991 15175 0 4620 5136 90.0 

YOYV 1994 31740 1 4780 5136 93.1 

______________________________________________________________________________________ 
119 

4. DEPOSITION 

a. Introduction 

Atmospheric deposition has been studied extensively throughout the world, beginning in the 1800’s 

in England, Sweden, Norway, and Germany. Research has primarily focused on the deposition of 

acidic pollutants and long-term acidification. Many publications describe current conditions, 

monitoring and modeling methods, and the results of acidification experiments. In the United 

States, research on acidification was first begun in 1962 at Hubbard Brook, New Hampshire. 

Subsequent work in the Adirondack lakes and other areas furthered the understanding of acid 

deposition effects. It is now recognized that, in addition to causing acidification, deposition of 

pollutants can affect many ecosystem characteristics, including nutrient cycling and biological 

diversity. 

Although much progress has been made to control sulfur dioxide and nitrogen oxide emissions, 

deposition of sulfur (S) and nitrogen (N) compounds continues to be a problem in North America 

and Europe (Hedin and Likens 1996). As a result, certain sensitive freshwater lakes and streams 

continue to lose acid-neutralizing capacity (ANC) and sensitive soils continue to be acidified. Other 

ecosystems, including forests, grasslands, estuaries, and N-limited lakes exhibit unwanted 

fertilization and other effects from excess N deposition. 

Federal Land Managers (FLMs) have documented the effects of S and N deposition on many air 

quality related values (AQRVs). Documented effects include acidification of lakes, streams, and 

soils; leaching of nutrients from soils; injury to high-elevation spruce forests; changes in terrestrial 

and aquatic species composition and abundance; changes in nutrient cycling; unnatural fertilization 

of terrestrial ecosystems; and eutrophication of estuarine and some lake systems. FLMs recognize 

that other undocumented effects may also be occurring. 

The FLAG deposition subgroup was formed to identify common approaches among these agencies 

for evaluating atmospheric deposition and its effects on AQRVs. In addition, the subgroup was 

directed to recommend methods for establishing critical deposition loading values (“critical loads”) 

and, where possible, recommend such critical loads for specific areas. These tasks were assigned to 

Phase I or Phase II, depending on their degree of difficulty. 

During the scoping process, the FLAG Deposition Subgroup determined that Phase I tasks would 

include the summarization of information currently available about deposition and its effects on 

FLM areas and the development of recommendations on methods to model and evaluate current 

and future deposition and its effects on AQRVs. In addition, critical load values, where available 

from previous FLM guidance documents, would be referenced. FLMs agreed that site-specific 

AQRV and critical load information would be maintained on FLM web sites, rather than included 

in the Phase I report. In this way, the information can be updated and the most recent versions 

made quickly available to the public. Some of this information is already available on FLM web 

sites, and the FLMs are committed to entering remaining available information as soon as possible. 

The subgroup recognizes that the development and refinement of site-specific critical load values 

for all FLM areas are crucial for AQRV protection. However, because of the complexity of this 

undertaking, and the lack of information for many areas, it was deferred to Phase II. 
120 

During Phase II, the subgroup will focus efforts on developing methods for establishing critical 

deposition loading values for FLM areas, and establishing critical loads for areas with adequate 

information. For areas lacking sufficient information to determine critical loads, strategies will be 

developed to obtain needed information. Previously established critical loads will be reviewed and 

refined as necessary. The subgroup will also explore alternative methods for estimating background 

deposition rates, including extrapolation techniques or modeling that considers the spatial scale of 

ecosystems and differences in elevation. Methods for addressing problems with dry deposition and 

cloud and fog deposition measurements will also be considered. In addition, Phase II will provide 

research or monitoring recommendations to improve our understanding of deposition and its 

effects, including effects on cultural resources. 

b. Current Trends in Deposition 

From 80%-99% of S emissions and from 83%-95% of nitrogen oxides emissions are anthropogenic 

(NAPAP 1991). As a result, most S and N deposition is anthropogenic in origin. The Clean Air Act 

mandated reductions in S and N emissions that should result in decreases in S and N deposition. 

Deposition monitoring data can be used to identify decreases in deposition. The National Atmospheric 

Deposition Program (NADP) provides one of the best and most comprehensive long-term records of 

wet deposition chemistry in the U.S. Results from a trends analysis of 1983-1994 data from 153 

NADP sites (Lynch et al. 1996) are shown on Figures D-2, D-3, and D-4. 

 

Figure D-2 shows that, between 1983-1994, wet precipitation sulfate concentrations declined 

significantly at 38% of monitored sites, presumably as a result of the Clean Air Act and mandated 

emissions reductions. Numeric declines were observed at the majority of the remaining sites. Sulfate 

concentrations increased significantly at only one site. A more recent analysis of 1995-1997 NADP 

data from eastern sites showed continuing declines in sulfate concentrations and wet depositions over 

much of the northeastern U.S. (Lynch et al. 2000). The EPA’s “National Air Quality and Emissions 

Trends Report, 1998,” also reported declines in the concentrations of sulfate in wet deposition, noting 

that the reductions were directly related to the large regional decreases in sulfur dioxide emissions 

resulting from Phase I of the Acid Rain program (U.S. EPA 2000).

Despite emissions reductions, many FLM areas are located where current sulfate, and therefore total S, 

deposition remains high and where deposition is in excess of estimated critical loads. A workgroup 

convened by the Ecological Society of America (ESA) in 1999 concluded that in some regions and 

ecosystems, current reductions of S emissions may be insufficient for ecological recovery to occur 

(ESA 2000). Surface water sulfate concentrations are generally not decreasing because of the 

desorption of previously deposited S from soils (Johnson and Henderson 1979), and surface S 

mineralization with pond and lake water level changes (Schindler 1998). Elevated surface water 

sulfate concentrations from past deposition is expected to persist for decades even with continued 

emission declines. Chronic high surface water sulfate levels reduce ANC, making ecosystems more 

vulnerable to chemical change during episodic events. 

Figure D-3 shows that there is no consistent trend in nitrate concentrations. The number of sites 

exhibiting increasing trends is nearly equal to the number exhibiting decreasing trends. However, the 

number of sites that experienced a statistically significant increase in nitrate (14%) was much greater 

than the number of sites that experienced a significant decrease in nitrate (1.3%). Figure D-4 shows an 

increase in ammonium concentrations at most sites, with statistically significant increases at 22% of 
121 

the sites, mostly in the West. Only one site had a significant decreasing trend. Given the increases in 

nitrate and ammonium, total N concentrations are clearly increasing at some locations. 

Estimates of natural background S and N precipitation concentrations and deposition can be made 

from certain reliable early precipitation chemistry data (Junge 1958), precipitation data from carefully 

selected remote areas such as Alaska and Argentina, and to some extent from present NADP data from 

coastal Oregon and Alaska (NADP 1982-1997). Except for coastal Oregon, present precipitation S and 

N concentrations throughout the contiguous states exceed these estimates of natural background 

levels, primarily due to anthropogenic emissions of S and N compounds. 

In this chapter, it is assumed that S is deposited into the environment primarily as sulfate ion and N is 

deposited primarily as nitrate and ammonium ions. Other ionic forms of S and N occur in the 

atmosphere, but information on their deposition into ecosystems is limited. For example, organic N 

may be important in some areas, but reliable measurement methods for organic N in atmospheric 

deposition are not widely available. 
122 

Figure D-2. Trends in sulfate ion concentration, 1983-1994 (Lynch et al. 1996). 

National Atmospheric Deposition Program I National Trends Network 

Trends in Sulfate lon Concentration 

1 983 through 1994 

'V Negative slope estimate, p>O .05 

"'Negative slope estimate, p<O .05 

I" 

£:.Positive slope estimate, p>0.05 

.&. Positive slope estimate, p<0.05 
123 

Figure D-3. Trends in nitrate ion concentration, 1983-1994 (Lynch et al. 1996). 

National Atmospheric Deposition Program I National Trends Network 

Trends in Nitrate I on Concentration 

1 983 through 1994 

'V Negative slope estimate, p>O .05 

"'Negative slope estimate, p<O .05 

, £:.Positive slope estimate, p>0.05 

.&. Positive slope estimate, p<0.05 
124 

Figure D-4. Trends in ammonium ion concentration, 1983-1994 (Lynch et al. 1996). 
125 

c. Identification and Assessment of AQRVs 

AQRVs sensitive to pollutant deposition have been identified in various documents published by 

the USDA/FS, NPS, and FWS, which are listed in the “General References” of Appendix H of this 

report. The FLMs have previously used a combination of approaches to identify AQRVs, 

including national and regional workshops, regional reviews, and site-specific studies. AQRV 

identification was based on information from peer-reviewed scientific literature and expert 

judgment. Because information on AQRVs may change as new data becomes available, the FLMs 

agree that AQRV information will be made available on FLM web sites to allow for updating and 

improve accessibility, as discussed in the Introduction to this chapter. 

Information on AQRVs for many USDA/FS Class I areas can be found at 

http://www.fs.fed.us/r6/aq/natarm. 

The USDA/FS is currently adding to and updating this information. 

NPS and FWS are currently developing a web site with AQRV information that will be linked to the 

NPS AirWeb at 

http://www.nature.nps.gov/ard 

and to the FWS National Wildlife Refuge System web site at 

http://refuges.fws.gov.

FLMs recommend that permit applicants consult with the appropriate FLM (Appendix F) to determine 

the need for an AQRV analysis and, if applicable, the methods for the analysis. 

All FLMs use a similar conceptual approach to identify AQRVs that reflects the FLMs’ interest in 

maintaining the integrity of ecosystem structure and function and protecting the most sensitive 

ecosystem components. AQRVs can be categorized by the type of ecosystem in which they are found, 

such as terrestrial, freshwater, and estuarine ecosystems. Each ecosystem and its AQRVs responds 

somewhat differently to deposition and approaches to evaluating deposition effects must therefore be 

developed accordingly. In terrestrial ecosystems, detection of changes in production, decomposition, 

and nutrient cycling processes provide information on deposition stress. In aquatic and estuarine 

ecosystems, detection of changes in water chemistry and aquatic community composition and 

structure provide similar information. Table D-1 summarizes AQRV indicators that may be used to 

assess effects in various ecosystems. 
126 

Table D-1. Indicators for monitoring and evaluating effects 

 from deposition of S and N. 

ECOSYSTEM INDICATORS FOR SULFUR DEPOSITION

Freshwater Chemical change (ANC depression), changes in 

phytoplankton and benthic community composition, 

species diversity, biomass 

Terrestrial Leaching of soil cations, soil acidification, mobilization of 

aluminum ions 

Estuarine Saltwater not sensitive to S deposition; leaching of 

nutrients may occur in sandy nearshore soils 

 

ECOSYSTEM INDICATORS FOR NITROGEN DEPOSITION

Freshwater Chemical change (ANC depression), changes in 

phytoplankton and benthic community composition, 

species diversity, biomass 

Terrestrial Changes in: litter and soil carbon and N dynamics; 

biomass; soil N processes; litter decomposition rates; soil 

microbe functional groups; soil organic matter quality and 

quantity; soilwater chemistry 

Estuarine Changes in: phytoplankton species composition and 

biomass; aquatic invertebrates; seagrass health and 

distribution; nutrient ratios; dissolved oxygen; trophic 

status 

Terrestrial, freshwater, and estuarine AQRVs are discussed below. In addition, methods to evaluate Sand N-induced deposition stress are discussed. 

Terrestrial Ecosystems

Terrestrial ecosystem AQRVs include flora, fauna, and soils. FLMs have identified, where possible, 

AQRVs, or characteristics of AQRVs, most likely to be sensitive to S and N deposition (“sensitive 

receptors”). For example, high-elevation spruce forests may be sensitive receptors. FLMs assess the 

condition of these sensitive receptors by evaluating some aspect of the receptor (the “sensitive receptor 

indicator”, or “indicator”). For example, an indicator for high-elevation red spruce forests is the 

occurrence and extent of winter foliar injury. In general, the FLM has focused on deposition effects to 

vegetation and chemical receptors in terrestrial ecosystems, with little emphasis on fauna. In addition, 

there is increasing awareness among FLMs that certain soil fauna (e.g., microorganisms and 

invertebrates) are very sensitive to deposition and can be used as sensitive receptors. 

In terrestrial ecosystems, sulfate production is regulated primarily by chemical processes (Johnson et 

al. 1983) and it is rarely a limiting nutrient. Soil response to acidic deposition can be evaluated by 

monitoring the leaching of essential soil cations, soil acidification, and mobilization of ionic 

aluminum. These processes have been studied both in field and laboratory experiments, and are 

defined in detail in the literature (Mollitor and Raynal 1983, Richter et al. 1983, Johnson et al. 1983, 

Reuss and Johnson 1986). Effects of S deposition can be detected by monitoring calcium and 
127 

magnesium ions and S in the litter layer and surface soils; calcium, magnesium, potassium, and 

sulfate ions in soil solution; cation exchange capacity (CEC); and base saturation. 

In general, biological AQRVs do not provide reliable indicators of S deposition in terrestrial 

ecosystems except under extreme S deposition. Lichens have been used in some areas as biomonitors 

to demonstrate spatial trends in S deposition, particularly in areas with pronounced S deposition 

gradients. For example, isotopic analysis of lichens from Mt. Zirkel Wilderness, Colorado, indicated 

that power plants in the nearby Yampa Valley were the source of elevated S in the lichens (Jackson et 

al. 1996). 

Unlike S, the production and mobility of N in ecosystems is regulated almost entirely by biological 

processes. N is a limiting nutrient in most terrestrial and estuarine ecosystems, and is seasonally 

limiting in many freshwater ecosystems. Most ecosystems can retain and process significant additions 

of N, with resulting increases in production and changes in species diversity, biomass, and nutrient 

cycling. However, these changes are usually considered to be undesirable in natural ecosystems. The 

ability to retain and process N varies significantly depending on watershed successional status, site and 

fire history, soil conditions, vegetation, and other non-human factors. When N inputs exceed an 

ecosystem’s assimilation capacity, N is lost or leached, usually as nitrate, from the soil and can be 

detected in adjacent streams or lakes. This may occur following a major disturbance such as fire, 

logging, land use change, grazing, agriculture, or where atmospheric N deposition or experimental 

inputs exceed what the ecosystem can assimilate (Fenn and Dunn 1989, Fenn 1991, Fenn et al. 1996, 

Adams et al. 1997). 

Studies in northern Europe (Dise and Wright 1995) found that European forests leached detectable 

levels of nitrate at inputs of about 10-25 kilograms N per hectare per year (kg N ha-1yr-1). Tundra and 

high-elevation alpine sites may leach N at much lower levels of input. Mountain watersheds in the 

western U.S. show signs of N leakage at wet deposition levels of 3-5 kg N ha-1yr-1 (Eilers et al. 1994; 

Williams et al. 1996; Williams and Tonnessen, in review). However, even high elevation, poorly 

vegetated ecosystems with limited soil development can process more than 80% of the atmospheric N 

input before it reaches the aquatic system (Campbell et al. 1995, Kendall et al. 1995). Although 

nitrogen leaching has often been used as an indicator of excess N deposition, major changes occur in 

below- and aboveground biomass, species diversity, and nutrient cycling long before N input levels 

are sufficient to cause nitrate leaching (NAPAP 1993, Tilman et al. 1997, Vitousek et al. 1997). For 

example, with ambient deposition rates of 7-10 kg N ha-1yr-1, a Minnesota Long-Term Ecological 

Research (LTER) grassland study observed shifts from native, warm-season grasses to low diversity 

mixtures dominated by cool-season grasses and a greater than 50% decline in species richness (Wedin 

and Tilman 1996, Tilman et al. 1997). Significant losses in terrestrial diversity may have already 

occurred over extensive areas of the U.S., particularly in forest understories, shrublands, grasslands, 

and in soil microbial communities. 

Because significant ecological changes may occur before nitrate loss can be detected, more sensitive 

indicators than nitrate leaching are needed to evaluate N deposition effects. Such indicators include 

changes in carbon and N dynamics of litter and soil and biomass (Aber and Driscoll 1997, Magill et al.

1997). With knowledge of inputs and small-scale N fertilization studies, changes in soil organic matter 

quality and quantity in response to N deposition can be evaluated. Soil microbial communities control 

the quantity and quality of N available to ecosystems and may be very sensitive indicators of N 

deposition. Changes in soil microbe functional groups or biomass may provide good estimates of 

ecosystem critical loads and incremental effects. Soil N mineralization, small root growth, and 

carbon:nitrogen ratios of soil and microbial biomass are also sensitive to N deposition. Evidence 
128 

suggests that current deposition rates may alter the production of dissolved organic carbon and 

organic N compounds in soils, which are important nutrient and energy sources for both terrestrial and 

aquatic ecosystems. These could also be used as indicators of N deposition effects. However, because 

there are many other variables that also affect soil processes, it may be very difficult to discern effects 

on any soil indicators that are solely attributable to N. 

Freshwater Ecosystems

AQRVs in freshwater ecosystems include lakes and streams and their associated flora and fauna. 

Sensitive receptors include water chemistry and clarity, phytoplankton, zooplankton, fish, amphibians, 

macroinvertebrates, and benthic organisms. Water chemistry indicators that respond to deposition 

include pH, ANC, conductance, cations and anions, metals, and dissolved oxygen. Physical indicators, 

such as water clarity, and biological indicators, including species diversity, abundance, condition 

factor and productivity of fish, amphibians, macroinvertebrates, and plankton can also be used to 

detect deposition effects in aquatic ecosystems. Much research has been done on the sensitivity of 

aquatic species to deposition, many of which are discussed in the 1990 National Acid Precipitation 

Assessment Program (NAPAP) State of Science report (NAPAP 1991a) and the 1998 NAPAP report 

(NAPAP 1998). 

Sulfur is not a limiting nutrient in freshwater ecosystems. However, there are small regions of the 

U.S., including some FLM areas, where a relatively high percentage of surface water is sensitive to 

present acidic inputs. In these areas, S deposition can cause decreases in ANC and pH. For these 

sensitive or low-ANC waters, the best approach to quantify S deposition effects is the procedure 

currently used, monitoring changes in ANC and pH. 

Nitrogen deposition, like S deposition, can cause episodic acidification of surface water in certain 

sensitive high-elevation ecosystems that have low-ANC headwater lakes and streams. Episodic 

acidification occurs in these areas when deposition is as low as 3-5 kg N ha-1yr-1 (Williams et al.

1996). 

Estuarine Ecosystems

AQRV sensitive receptors in estuarine ecosystems include plankton, seagrasses, and water chemistry 

and clarity. Associated coastal forest and dune soils may also be useful as sensitive receptors. Water 

and soil nutrient concentrations, phytoplankton species composition and abundance, seagrass health, 

and dissolved oxygen concentrations can be used to evaluate deposition effects. 

In estuaries, S is not a limiting nutrient. In addition, estuarine waters are highly buffered and, 

therefore, not subject to acidification. However, many coastal forest and dune soils are dominated by 

sandy soils that are sensitive to leaching of limiting nutrients because of very low cation exchange 

capacity (Au 1974). Monitoring for change in estuarine areas with high S deposition should therefore 

focus on soil ion mobility. As soil calcium and magnesium levels are generally adequate because of 

deposition from marine sources, potassium is likely the only limiting nutrient subject to significant 

loss by sulfate leaching. 

The role of N in estuaries is probably the best-documented example of anthropogenic alteration with a 

literature record dating back to the 1950s. Production and use of fertilizers, land use changes, and 

fossil fuel combustion have greatly increased the available N, normally a limiting nutrient, which 

enters coastal waters. This has increased estuarine production and accelerated the process of 
129 

eutrophication. Eutrophication can result in dramatic algae blooms, anoxia, the production of toxic 

hydrogen sulfide gas, and species extirpation in estuarine ecosystems. Human induced eutrophication 

has been documented for many areas along the Atlantic and Gulf coasts, including the Chesapeake 

Bay, Tampa Bay, Sarasota Bay, Florida Bay, and Long Island Sound. 

A number of FLM areas along the Atlantic and Gulf coasts contain significant coastal waters that may 

be sensitive to eutrophication. Little is known about excess N effects in most of these areas, although 

eutrophication is well documented in Florida Bay, located in Everglades National Park. Also, recent 

evidence indicates that coastal waters in Chassahowitzka Wilderness (Florida) experience N-induced 

algal blooms (Dixon and Estevez in draft). In most coastal waters, 10-45% of the N entering the 

system is atmospheric, either from direct deposition to surface water or deposition to the watershed. 

Complete elimination of atmospheric N inputs would not entirely mitigate ecosystem change due to N 

because of the substantial contributions from agricultural and urban runoff. However, for most 

estuaries, any reduction in N input would be beneficial in restoring ecosystem structure and function. 

The monitoring procedures recommended, and currently used, in estuaries are similar to those used in 

freshwater, with emphasis on incremental changes in plankton, aquatic plant, benthic, and invertebrate 

community composition; species diversity, distribution, and biomass; and ecosystem trophic status. 

Significance of Long-Term Monitoring to Evaluate Trends and Validate Modeling

Long-term monitoring is critical to evaluate trends in deposition and deposition effects. Monitoring 

programs should concentrate not only on areas with high past and/or present sulfate, nitrate, or 

ammonium deposition, but also in areas that are very sensitive to deposition and in areas where 

deposition is expected to increase. For selected monitoring sites, the FLM should (1) obtain ion 

deposition data for the site, as from NADP or CASTNet, (2) identify sensitive AQRVs and appropriate 

variables to monitor, (3) evaluate the present condition of the sensitive AQRVs, (4) determine the 

degree to which results from one site can be extrapolated to other FLM areas in the region, and lastly 

(5) implement a long-term monitoring program, using carefully selected variables. 

Long-term monitoring data are also needed to support and validate models used to predict deposition 

and deposition effects, including the effects of increases or decreases of S and N on ecosystems. Long 

term studies in both aquatic and terrestrial ecosystems such as Hubbard Brook, Lake Tahoe, and the 

Experimental Lakes Area have provided useful information for modeling (Bormann and Likens 1967, 

Holm-Hanson et al. 1976, Likens and Bormann 1977, Leonard et al. 1979, Byron and Eloranta 1984, 

Schindler et al. 1985, Schindler 1987, Schindler et al. 1990, Jassby et al. 1995). NAPAP and the 

National Science Foundation LTER program have addressed monitoring to meet modeling needs in 

both terrestrial and aquatic ecosystems. 

Data requirements to support models vary, but the quality of input data will determine the quality of a 

model’s predictions. Modeling is further discussed in the “Other AQRV Identification and 

Assessment Tools” section of this chapter. 

d. Determining Critical Loads 

 

Critical load is defined by FLMs as “the concentration of air pollution above which a specific 

deleterious effect may occur.” Critical loads have been widely accepted in Europe and Canada as a 

basis for negotiating control strategies for transboundary air pollution (Posch et al. 1997). 
130 

In Canada, researchers have estimated the critical loads of S in wet deposition necessary to protect 

moderately sensitive lakes in eastern provinces. That value, equivalent to 6.7 kg ha-1yr-1 of S in wet 

deposition, was used by Canada to argue for the U.S. to implement the Clean Air Act Amendments 

of 1990, which call for the initial reduction of sulfur dioxide emissions in the eastern U.S. and later 

from all electric utilities nationwide. With additional data on lake and stream chemistry available for 

sensitive systems in Nova Scotia, Ontario, and Quebec, the Canadians are now recommending a more 

stringent critical load, equivalent to 2.7 kg ha-1yr-1 of wet deposition S. 

In both European countries and in North America, attention has expanded beyond ecosystem damage 

caused by S deposition to ecosystem damage caused by N deposition. In some European forests, 

chronically high N deposition has exceeded the assimilation capacity of local ecosystems, resulting in 

the release of nitrate into surface waters (Dise and Wright 1995). Watersheds that are leaking nitrate 

into surface waters during the growing season, are referred to as "N saturated" (Aber et al. 1989). 

Nitrogen saturation has been linked to forest decline in Europe (Schulze 1989). Based on a set of 

regional N addition experiments conducted at sites in northern Europe (NITREX), Wright (1995) 

recommended a N critical load of less than 10 kg ha-1yr-1 to protect European forests and freshwaters 

from N saturation. However, this critical load does not protect ecosystems from the changes caused 

by N deposition prior to actual N saturation, including shifts in composition and abundance of soil 

fauna species and alterations in soil chemistry. 

In the United States, two states have attempted to set deposition standards or critical loads to protect 

sensitive ecosystems. In 1982, the State of Minnesota passed the Acid Deposition Control Act to limit 

wet sulfate deposition to 11 kg ha-1yr-1, which is equivalent to 3.7 kg S ha-1yr-1. At this sulfate level, 

precipitation pH was likely to remain above 4.7, which would protect lakes with ANC less than 50 

microequivalents per liter (μeq l-1). This critical load was to be achieved by controls on large sources 

of sulfur dioxide in Minnesota. As of 1990, monitoring by state officials showed no evidence of lake 

acidification under the sulfur dioxide control program. However, the efficacy of this control strategy 

is still uncertain, because as much as 90% of the sulfate deposited in northern Minnesota may have 

sources outside of the state (Orr et al. 1992). 

In 1989, the California legislature adopted the Atmospheric Acidity Protection Act, which required 

the Air Resources Board (CARB) to "develop and adopt standards, to the extent supportable by 

scientific data, at levels which are necessary and appropriate to protect public health and sensitive 

ecosystems from adverse effects resulting from atmospheric acidity" (CARB 1993). An assessment 

of existing data identified the high elevation watersheds, surface waters, and mixed conifer forests of 

the Sierra Nevada and the Los Angeles Basin as sensitive ecosystems. CARB analyses suggested that 

appropriate standards would include a critical load value for inorganic N to protect forests, and 

critical loads for both N and S to protect poorly buffered lakes and streams. However, no acidity 

standards to protect human health or critical loads to protect ecosystems have been set in California to 

date. 

The Clean Air Act Amendments of 1990, Title IV, section 404, called on the Environmental 

Protection Agency (EPA) to prepare a report on the feasibility and effectiveness of setting deposition 

standards nationwide to protect sensitive aquatic and terrestrial resources. The completed report 

includes a number of modeling analyses that project the effect of reductions in both S and N 

deposition in areas studied during NAPAP. EPA concluded that deposition standards could not be set 

at this time because of 1) the lack of clearly defined policy regarding appropriate or desired goals for 

protecting sensitive aquatic or terrestrial resources, and 2) key scientific uncertainties, particularly 

regarding nitrogen watershed processes. In addition, EPA recognized that a national deposition 
131 

standard might be inappropriate because of differences among ecosystems. However, in response to 

public comments on the report, EPA stated that “Given an adequate level of monitoring and 

assessment data, Class I areas could serve as potential targets for standard setting activities.” (U.S. 

EPA 1995) 

Critical Loads in FLM Areas

 

In the Clean Air Act, as amended in 1977, Congress gave FLMs an “affirmative responsibility” to 

protect AQRVs from the adverse effects of air pollution. Congress’ intent was, “...In cases of doubt 

the land manager should err on the side of protecting the air quality-related values for future 

generations...” (Senate Report No. 95-127, 95th Congress, 1st Session, 1977). In an effort to ensure 

AQRV protection, FLMs have established critical loads for many FLM areas. FLMs agree that a 

critical load should protect the most sensitive AQRVs within each FLM area and should be based on 

the best science available. As new scientific information becomes available, critical loads should be 

reviewed and updated. Critical loads should ensure that no unacceptable change occurs to the 

resource. 

FLMs have previously used a combination of approaches to establish critical loads, including national 

and regional workshops, regional reviews, and site-specific studies (see Appendix H). In all cases, the 

FLMs have used peer-reviewed scientific literature and expert judgment to make their decisions. For 

example, the NPS has established critical loads for several national parks through regional reviews 

that have evaluated existing information on air quality, deposition, and effects on AQRVs in national 

parks. For these reviews, NPS grouped parks by region and ecosystem type, including the Pacific 

Northwest, the Colorado Plateau, and the Rocky Mountains, and conducted an empirical assessment 

of the status of aquatic and terrestrial resources. An analysis of deposition effects was done, using 

current deposition data for S and N and effects information from field observations and research. In 

the Pacific Northwest region, this analysis led researchers to recommend guidelines for critical loads 

of S and N to protect sensitive resources, particularly low-ANC lakes, streams and ponds. These 

guidelines for critical loads will be available on the NPS AirWeb site in the near future at: 

http://www.nature.nps.gov/ard. 

The FWS is also committed to establishing critical load guidelines to protect sensitive resources. 

These guidelines for critical loads will be available through the FWS National Wildlife Refuges site 

at: 

http://refuges.fws.gov. 

 

The USDA/FS has conducted a series of national and regional workshops to establish critical loads 

and concern thresholds. In the late 1980s, the USDA/FS published prototype methods for evaluating 

the effects of acid deposition on AQRVs, including A Screening Procedure to Evaluate Air Pollution 

Effects on Class I Wilderness Areas (Fox et al. 1989) and Guidelines for Measuring the Physical, 

Chemical, and Biological Condition of Wilderness Ecosystems (Fox et al. 1987). Subsequently, the 

USDA/FS held regional workshops to develop screening procedures for new air pollutant emissions 

sources. These workshops were comprised of national and regional USDA/FS land managers, 

deposition experts from the academic and air pollution research community, and agency air quality 

professionals. Dependent on the workshop leadership, each regional workshop followed a slightly 

different process and a variety of outputs and formats resulted. However, all workshops used a 

collaborative process to determine S and N deposition rates that would pose a risk to the aquatic and 

terrestrial ecosystems protected in FLM areas, while addressing the scientific uncertainty inherent in 
132 

ecosystem response to acidic deposition. Critical load guidelines for many USDA/FS Class I areas 

are published in workshop reports (see Appendix H) and are available at: 

http://www.fs.fed.us/r6/aq/natarm. 

The USDA/FS is currently adding to and updating this information. 

 

As resources permit, during Phase II of FLAG, the subgroup will develop methods for establishing 

critical deposition loading values for all FLM areas and recommend critical loads for areas where 

adequate information exists. For areas lacking sufficient information to determine critical loads, 

strategies will be developed to obtain needed information. 

e. Other AQRV Identification and Assessment Tools 

In addition to AQRV monitoring, there are several tools available to the FLM for identifying AQRVs 

and assessing the response of sensitive AQRVs to pollutant deposition. These include the aquatic 

effects expert system component of the FWS/NPS Air Synthesis, the Natural Resource Information 

System – Air Module (NRIS-Air), and deposition models such as the Model of Acidification of 

Groundwater in Catchments (MAGIC) and MAGIC-With Aggregated Nitrogen Dynamics (MAGICWAND).

Air Synthesis

Air Synthesis is an information management and decision-support computer system under 

development by NPS and FWS. Air Synthesis is designed to assist FLMs in determining potential 

effects of pollutants on AQRVs. It contains information on air quality and its effects in parks and 

wildernesses as well as natural resource data and annotated bibliographies of current literature on 

deposition. An interactive expert system module is under development for inclusion in Air Synthesis 

to allow FLMs to assess the current status of freshwaters and determine if these resources are likely 

to be affected by deposition of S or N. The aquatic effects expert system is being developed by 

regional scientists. This system will allow FLMs to input existing surface water data for lakes and 

streams to determine: (1) the acidification status of the waters, (2) the likely cause of high 

concentrations of acid anions (e.g., deposition, land use, organic inputs) and, (3) the sensitivity of the 

waters to increases in N or S deposition. Results can be displayed in a geographic information system 

(GIS) image that color-codes the acidification status of lakes and streams. In addition, the expert 

system evaluates the completeness and the amount of uncertainty in water chemistry data sets. Air 

Synthesis will be available through the NPS AirWeb at: 

http://www.nature.nps.gov/ard 

or the FWS National Wildlife Refuge System web site at: 

http://refuges.fws.gov. 

Natural Resource Information System – Air Module (NRIS-Air)

The Air Module is part of the USDA/FS Natural Resource Information System that integrates various 

physical, biological and socioeconomic data within a system of database, map-based spatial 

information, and analytical tools. Version 1.0 of NRIS-Air, released in November 1998, tracks 
133 

AQRVs, sensitive receptors and indicators for each of the USDA/FS Class I areas. The water 

submodule provides data storage, reports, and tools for evaluating locally entered water quality and 

wet deposition data. It also integrates the NADP data set and the entire National Surface Water 

Survey including the Eastern and Western Lakes Surveys and the National Stream Survey. Future 

NRIS-Air versions under development will provide the information structure for visibility, flora, 

fauna, soil, geologic resources, cultural resources, and air quality data, as well as providing an air 

pollution permit tracking system. 

Information from NRIS-Air, including USDA/FS Class I area AQRV information, is available at: 

 http://www.fs.fed.us/r6/aq/natarm. 

Deposition Effects Models

A number of watershed process models have been developed and tested in an attempt to simulate the 

effects of S and N on soils, forests, and surface waters. These models are used by FLMs to predict 

effects from increases in deposition and vary from detailed, compartment models of watersheds to 

lumped parameter models that do not track different ions through each soil compartment. For a 

review of models developed under NAPAP see NAPAP 1991. 

A commonly applied watershed model is MAGIC. MAGIC was first developed for eastern U.S. 

watersheds and then extensively tested and validated throughout Europe and North America (Cosby 

et al. 1985, 1995, 1996). The model was used by NAPAP in its 1990 Integrated Assessment to 

project surface water chemistry resulting from various deposition scenarios (NAPAP 1991b). In 

another application in the eastern U.S., MAGIC has been linked with a simple, empirical, 

dose/response fish model developed at University of Virginia, that makes it possible to predict 

changes in fish productivity based on modeled changes in streamwater chemistry. 

As a result of NAPAP, there was increased awareness of the potential impacts of inorganic N 

deposition on watersheds and surface waters. In response, the MAGIC model was updated with a 

module called With Aggregated Nitrogen Dynamics (WAND). MAGIC-WAND is a process-based 

model that uses site-specific information on hydrology, soils, and hydrochemistry. The model 

predicts changes through time in lake or stream chemistry. These time-series of changes in pH and 

ANC can subsequently be used by FLMs to calculate critical S or N loads for watersheds. 

MAGIC-WAND has been extensively tested in the Adirondacks and at watersheds in Maine. For 

example, the Bear Brook Watershed Manipulation Project uses MAGIC-WAND to predict the effects 

of experimentally added N and S on a test watershed. MAGIC-WAND has also been applied to 

watersheds in FLM areas in the Cascades, the Sierra Nevada, the Rocky Mountains, and the Wind 

River Range in an effort to quantify critical S and N loads to aquatic and terrestrial resources. In the 

southeastern U.S., MAGIC-WAND is being used under the auspices of the Southern Appalachian 

Mountains Initiative (SAMI) to predict the effects of future deposition scenarios on FLM areas. 

Future SAMI modeling efforts will link watershed model results with fish dose/response models. The 

ultimate goal is to calibrate MAGIC-WAND with landscape level data in order to set regional critical 

loads. 

Other models are also in use. For example, the USDA/FS Rocky Mountain Region recommends 

using either CALPUFF or ISCST (or other approved models) to estimate S and N deposition. The 

Screening Methodology for Calculating ANC Change to High Elevation Lakes (USDA Forest Service 
134 

2000) summarizes procedures for estimating total deposition of S and N. The document also 

recommends computations for estimating alkalinity changes in lakes caused by increases in S and N 

deposition. Another model, the Nutrient Cycling Model (NuCM) has been used in the East to predict 

the effect of changes in deposition on nutrient concentrations in soils and vegetation. 

f. Recommendations and Guidance for Evaluating Potential Effects from Proposed Increases 

in Deposition to an FLM Area 

 

FLMs often request that proponents of new emissions sources or modifications of existing sources 

near FLM areas provide sufficient information for the FLM to evaluate the potential effects of 

emissions increases on AQRVs. FLMs have provided guidance for applicants through guidance 

documents, correspondence, meetings, and phone consultations. This chapter summarizes current 

guidance for the evaluation of new emissions on deposition and sensitive AQRVs and includes 

recommendations for: 

• the types of data, information, and analysis needed before a permit can be considered complete, 

including analytical and modeling protocols for a proponent’s use in conducting an AQRV impact 

analysis; 

• approaches and sources of appropriate values for estimating wet and dry deposition; and 

• permit conditions to mitigate source impacts. 

These recommendations can most easily be described using a flow chart. Figure D-1 summarizes the 

approaches to be taken to evaluate a proposed action. 
135 

No/Unknown

Yes

START

Current

 adverse 

effects to AQRVs

from deposition/

Critical load 

exceeded

?

Yes

Unknown

No

New 

emissions 

cause or contribute to 

adverse effects/Critical

 load exceeded

?

FLM may recommend

elements of "a" or "b"

or (if necessary) "c"

 a. The applicant should use one or more of the following:

 - Stricter (than BACT) controls (e.g., Lowest Achievable Emission Rate [LAER]).

 - Emission offsets located in an area that, considering geographic and meteorological

 factors, will benefit the impacted wilderness or park, as demostrated by modeling.

 - Regional modeling to identify sources contributing significantly to deposition 

 adverse effects; SIP revision to reduce emissions contributing to adverse effects.

 (See text for discussion of mitigation options.) 

 b. Deposition and deposition effects monitoring/research in the FLM area.

 c. Denial of permit.

FLM unlikely

 to object to permit

FLM unlikely to

object to permit;

may recommend "b"

Figure D-1. FLM resonse to potential deposition effects from new 

emissions sources.

Figure D-1. FLM response to potential deposition effects from new 

emissions sources.
136 

The flowchart begins with the question, “Are there currently adverse effects from pollutant 

deposition to AQRVs in the FLM area?” To answer this question, the FLM needs information on 

deposition-sensitive AQRVs, deposition loads at which these AQRVs are affected (i.e., critical loads), 

and the current pollutant deposition rates in the area. In areas where no information is available, 

information from a nearby, or ecologically similar area, may be used. An adverse effect may be 

expected to occur if the critical load is exceeded for an area. AQRV and critical load information are 

discussed earlier in this report. Procedures for estimating current pollutant deposition rates are 

summarized in the section, “Estimation of Current and Future Deposition Rates.” After considering 

this information, the FLM determines if adverse effects to AQRVs already exist at an area. If adverse 

effects are present, the FLM may recommend that “a” or “b” or both of Figure D-1 are included as 

permit conditions. If these recommendations, or some combination of them, cannot be implemented, 

the FLM is likely to recommend denial of the permit. 

 

If there are no current documented adverse effects from pollutant deposition to AQRVs, or there is a 

lack of information on deposition and deposition effects in the area (and information from nearby or 

ecologically similar areas is unavailable), the FLM may ask, “Will the proposed action cause an 

adverse effect to AQRVs?” The information needed to answer this question includes the information 

listed above regarding AQRVs, critical loads, and current deposition rates. In addition, an estimate is 

needed of the future predicted deposition rate. Procedures for this estimate are found in the 

“Estimation of Current and Future Deposition Rates” section of this report. 

With this information, the FLM can determine if the proposed action is likely to cause an adverse 

effect to AQRVs. If the answer is no, or unknown, the FLM would not object to the action because of 

potential deposition effects. The FLM may still, however, object to the action for other reasons 

including an inadequate best available control technology analysis, predicted National Ambient Air 

Quality Standards violations, predicted Class I increment impacts, or other predicted AQRV impacts. 

If the available information is insufficient for the FLM to determine if the proposed action will cause 

an adverse effect to AQRVs, the FLM may ask for deposition and deposition effects monitoring 

and/or research in the FLM area (i.e., item “b”). If the answer is yes and the proposed action will likely 

cause an adverse effect to AQRVs, the FLM may recommend permit conditions that ensure 

mitigation, including stricter emissions controls and effective emissions offsets (i.e., item “a”). If no 

mitigation is possible, the FLM is likely to recommend denial of the permit. 

Available Deposition Monitoring Data

Atmospheric pollutants are deposited to ecosystems primarily through wet deposition and dry 

deposition. FLMs participate in national monitoring programs to monitor wet and dry deposition, 

including the National Atmospheric Deposition Program (NADP) and the Clean Air Status and Trends 

Network (CASTNet). A 1999 report, “The Role of Monitoring Networks in the Management of the 

Nation’s Air Quality,” (CENR, 1999) identified these two networks as being critical for characterizing 

baseline air quality data in the U.S. 

Wet Deposition 

 

Wet deposition includes rain, snow, fog, cloudwater, and dew. In most FLM areas, rain and snow are 

the primary contributors to wet deposition. However, in some high elevation areas, fog, cloudwater, 

and dew are significant contributors, as discussed below. 

Because rain and snow are the primary constituents of wet deposition at most FLM areas, the FLM 

generally relies on data from NADP to evaluate wet deposition of pollutants. NADP samplers collect 
137 

rain and snow and NADP has documented deposition for many years in a nationwide network that 

currently includes over 220 monitoring sites. The network collects data to evaluate spatial and 

temporal long-term trends in precipitation chemistry. The precipitation at each site is collected weekly 

and sent to a central analytical laboratory for analysis of hydrogen (acidity as pH), sulfate, nitrate, 

ammonium, chloride, and base cations, including calcium, magnesium, potassium, and sodium. Data 

and isopleth maps of pollutant concentrations and deposition are available on the NADP web site at: 

http://nadp.sws.uiuc.edu/ 

FLMs agree that it is preferable to obtain NADP data from the web site, rather than summarizing wet 

deposition data in this report. In this way, current data can be easily accessed by FLMs and the public. 

Approximately 50 FLM areas have NADP samplers in or immediately adjacent to them. Because 

some of these areas are classified as wilderness, FLMs install sampling equipment in adjacent nonwilderness areas in order to preserve the wilderness character of the area. Ambient air in these adjacent 

areas is considered representative of air in the wilderness area. 

A number of FLM areas do not have an NADP sampler in or adjacent to them. Where possible, the 

FLM has identified an NADP site whose data may be used to characterize deposition at the area. This 

information is appended to this Deposition chapter (Table D-2). Deposition rates generally increase 

with elevation and deposition in high-elevation areas may be difficult to characterize with data from a 

lower-elevation NADP site. FLM consultation may be necessary to estimate deposition in these areas. 

 

Areas that experience significant deposition from fog and cloudwater or large amounts of snow may 

need to use alternate sampling methods and data in addition to NADP protocols and NADP data to 

characterize them. Wet deposition in these areas may need to be sampled with alternate methods, 

including cloudwater samplers and snowpack sampling or estimated by modeling. At sites where such 

data or modeled estimates are available, they should be used to calculate total deposition. At mountain 

sites frequented by clouds and fog, deposition from clouds may equal or exceed that from 

precipitation. Cloud water is generally more acidic and contains higher concentrations of base cations 

than rain water; therefore, it can contribute significantly to total loadings of S and N (Hemmerlein and 

Perkins 1992). Various methods have been developed to measure deposition from cloudwater. The 

Mountain Acid Deposition Program (MADPro) used automated cloud water collectors to sample at 

three high-elevation eastern sites (Anderson et al. 1999). Forests covered by fog for significant 

periods of time may be especially susceptible to injury from acid deposition. Acidic cloud water has 

predisposed red spruce in the high elevations of the northeast U.S. Appalachians to winter injury and 

cumulative impacts with other biotic and abiotic stresses have caused mortality. The contribution of 

clouds and fog to deposition at high elevations may overshadow both deposition from precipitation 

and dry deposition (Hidy 1998). The U.S. EPA estimated that as a result of cloud cover, high 

elevation forests might experience four times the amount of total pollutant deposition as lower 

elevation forests without cloud cover (NAPAP 1991). High elevation lakes are also impacted by fog 

and clouds, as well as rain and snow. Measurements in high elevation areas that do not include all 

contributions to wet deposition will result in under-estimates. 

Modeling has been used to estimate total wet deposition in some areas. For example, the Southern 

Appalachian Man and the Biosphere Cooperative (as part of the Southern Appalachian 

Assessment) has used NADP data, topographical data, and meteorological data to model wet 

deposition loading at locations in the southeastern U.S. 
138 

Dry Deposition 

 

Dry deposition includes gases, aerosols and particles. The primary gases involved with N and S 

deposition are ammonia (NH3), nitric oxide (NO), nitrogen dioxide (NO2), nitric acid (HNO3), and 

sulfur dioxide (SO2), while the primary particles are nitrate (NO3

-

), ammonium (NH4

+

), and sulfate 

(SO4

2-) ions (Hanson and Lindberg, 1991). Ammonia, NO, NO2 and SO2 are taken up by plants 

through stomata, while HNO3, due to its high deposition velocity, is deposited to plant surfaces in 

addition to being taken up by stomata. Nitrate, ammonium, and sulfate particles deposit to surfaces 

(Bytnerowicz and Fenn, 1996). 

Dry deposition is much more difficult to estimate than wet deposition. The estimation of dry 

deposition rates requires information on the ambient concentrations of pollutants, meteorological data, 

and information on land use, vegetation, and surface conditions, all of which are site-specific. Because 

of this site-specificity, it is difficult to spatially extrapolate dry deposition data as is often done for wet 

deposition data. 

In general, FLMs rely on data from CASTNet for estimates of dry deposition in FLM areas 

 http://www.epa.gov/castnet/ CASTNet was developed by EPA, as a 

result of the Clean Air Act Amendments of 1990, and currently includes over 70 sites. These include a 

combination of former National Dry Deposition Network sites, Park Research and Intensive 

Monitoring of Ecosystems Network sites (PRIMENet), and others. Dry deposition is measured at 26 

NPS areas and 2 USDA/FS areas. FLMs agree that it is preferable to obtain CASTNet data from the 

web site, rather than summarizing dry deposition data in this report. In this way, current data can be 

easily accessed by FLMs and the public. 

Other methods for measuring dry deposition are available. For example, information on vertical 

changes in concentrations of major gases and particles of interest over plant canopies can be used for 

calculation of deposition of these compounds to forests and other ecosystems (Hicks et al., 1987). 

Models, such as “Big-Leaf” (Baldocchi et al., 1987) allow estimating dry deposition to uniform 

canopies, such as agricultural crops or lowland forests. However, no models have been developed so 

far for reliable estimates of deposition of gases and particles to forests and other ecosystems in 

complex mountain terrain (Bytnerowicz et al., 1997). Therefore, no good large-scale estimates of dry 

deposition are available for western U.S. forests. 

Another approach to evaluating dry deposition is net throughfall technique. By measuring 

concentrations of ions in throughfall (bulk precipitation) and after subtracting concentrations of the 

same ions in precipitation in an open area, fluxes of ions such as nitrate, ammonium, and sulfate can 

be calculated. A branch washing technique is similar to the net throughfall approach and is used when 

no wet precipitation is present. The pre-washed branches are exposed to ambient air for a certain time 

period and then carefully rinsed with water (Lindberg and Lovett, 1985). Information about amounts 

of nitrate, ammonium and sulfate rinsed from branches of a known surface area, time of exposure, and 

leaf area index of a given forest stand allow the calculation of fluxes of the measured ions to trees. 

Adding stomatal uptake of gases (calculated from information on gas concentration and stomatal 

conductance), and estimates of deposition to other landscape forms (such as soils and rocks) allow for 

quite reliable estimates of dry deposition at a forest stand level (Bytnerowicz et al., 2000). Such 

estimates have been made for the subalpine zone of the eastern Sierra Nevada and mixed conifer 
139 

forests on the western Sierra Nevada and the San Bernardino Mountains (Bytnerowicz and Fenn, 

1996; Bytnerowicz et al., 1999). Both the net throughfall and branch washing techniques, although 

providing relatively accurate estimates of deposition to certain ecosystems, cannot be applied to every 

type of vegetation. These techniques work well for conifers with relatively thick cuticles. For plants 

with thinner cuticle, extraction of ions from plant interior or transcuticular uptake of deposited ions 

may not allow for making good estimates of dry deposition to plant surfaces. 

Recent developments, such as passive samplers that allow for relatively inexpensive determinations of 

nitric oxide, nitrogen dioxide, ammonia, nitric acid and sulfur dioxide concentrations, provide some 

promising opportunities for large-scale estimates of distribution of these pollutants. This, together 

with information on landscape-level vegetation coverage, leaf area index, and deposition velocity of 

the monitored pollutants, will allow calculating deposition of the measured gases to various landscape 

forms. Although this approach would not include deposition fluxes of particulate pollutants, a large 

portion of dry N and S deposition (gases) would be covered. Information on fluxes of the N and S 

particulate component (nitrate, ammonium, and sulfate ion concentrations) can be estimated based on 

their concentrations from annular denuder/filter pack systems or other comparable techniques and 

literature values of deposition velocities of these ions. 

For many FLM areas, detailed site-specific information and monitoring needed for dry deposition 

measurements are not available. Therefore, the FLM may choose to recommend a reasonable estimate 

of dry deposition. NAPAP’s 1991 summary report concluded that dry deposition of sulfur is 30-60% 

of the total (wet plus dry) deposition at regionally representative sites; dry deposition of nitrogen is 30-

70% of the total (wet plus dry) deposition at regionally representative sites (NAPAP 1991a). An 

analysis of one year (1991) of NADP, CASTNet, and IMPROVE (Interagency Monitoring of 

Protected Visual Environments) data from national parks and wildernesses found that wet deposition 

dominated total deposition in both the East and the West. Dry deposition of sulfur was 20-50% of the 

total; dry deposition of nitrogen was 30-60% of the total (Hidy 1998). These estimates, and similar 

ones, have led to the common assumption that dry deposition is approximately 50% of the total 

deposition. Therefore, for many FLM areas without on-site or nearby representative dry deposition 

sampling, the FLM may recommend that dry deposition is equal to wet deposition. The FLM 

recommends this as a “best available estimate,” recognizing that in some areas it may result in underor over-estimating total deposition. Total deposition, which is the sum of wet plus dry deposition, 

therefore equals twice the wet deposition. 

In summary, 

Total Deposition = Wet Deposition + Dry Deposition 

Or, 

Total Deposition = 2 x Wet Deposition, assuming Dry Deposition = Wet Deposition 

Table D-2 identifies monitoring stations in or near FLM areas for estimating wet and dry deposition 

values. For some areas the FLM assumes that dry deposition equals wet deposition, recognizing that 

this may result in under- or over-estimates of total deposition. The table provides information on the 

appropriate dry deposition data to use at sites where data are available. 

FLMs will continue to participate in monitoring and research to further our understanding of dry 

deposition dynamics and improve our measurements of dry deposition. 
140 

Other Deposition Measurement Methods 

Pollutant deposition, particularly in areas where traditional wet and dry deposition sampling is 

impractical, can also be estimated by other methods. These methods include bulk samplers that collect 

both wet and dry deposition and snowpack measurements that estimate the total amount of pollutants 

in the snow column at the time of maximum snow accumulation. Special methods have also been 

developed for collecting fog and cloud water (Anderson et al. 1999). 

 

In addition, methods are being developed to estimate dry deposition rates from pollutant 

concentrations obtained by IMPROVE fine particle samplers. IMPROVE samplers are located at 

many FLM areas and expanded coverage is planned for 1999. 

Modeling Deposition Rates 

Deposition from existing sources can be estimated from deposition monitoring data, but contributions 

to deposition from the proposed source and other sources permitted but not yet operating must be 

modeled. 

Modeling should be done in accordance with recommendations developed by the Interagency 

Workgroup on Air Quality Modeling (IWAQM) Phase 2: 

 

http://www.epa.gov/scram001/7thconf/calpuff/phase2.pdf. 

IWAQM provides the procedures that can be used to estimate S and N deposition from a proposed 

source and other sources permitted but not yet operating. The FLMs propose that these procedures be 

used to estimate S and N deposition. For S deposition, the wet and dry fluxes of sulfur dioxide and 

sulfate are calculated, normalized by the molecular weight of S, and expressed as total S. For N 

deposition, IWAQM recommends that the wet and dry fluxes of nitric acid (HNO3) and nitrate (NO3

-

) 

and the dry flux of nitrogen oxides (NOx) be calculated, normalized by the molecular weight of N, and 

expressed as total N. In addition, the FLMs agree that wet and dry fluxes of ammonium sulfate 

((NH4)2SO4)) and ammonium nitrate (NH4NO3) should be calculated, normalized by the molecular 

weight of N, and added to the estimate of total N. Therefore, total N deposition is the sum of N 

contributed by dry and wet fluxes of HNO3, NO3

-

, (NH4)2SO4, and NH4NO3 and the dry flux of NOx. 

The FLMs recognize that the ammonia (NH3) in these compounds is derived from both man-made and 

natural sources. Free gaseous NH3 has a high deposition velocity and tends to deposit quickly. 

However, if sulfates and nitrates (which are primarily man-made) are present in the atmosphere, free 

NH3 quickly reacts to form (NH4)2SO4 and NH4NO3. These compounds, because of their fine particle 

size and slower deposition velocity than free gaseous NH3, can be transported long distances and 

deposited in a FLM area, adding to the total N deposition loading. 

 

An appropriate estimate of ambient free gaseous NH3 is needed for the modeling analysis. IWAQM 

refers to Langford et al. (1992), who suggest that typical (within a factor of 2) background values of 

NH3 are: 10 parts per billion (ppb) for grasslands, 0.5 ppb for forest, and 1 ppb for arid lands at 20o

C. 

Langford et al. (1992) provide strong evidence that background levels of NH3 show strong dependence 

with ambient temperature (variations of a factor of 3 or 4) and a strong dependence on the soil pH. 

However, given all the uncertainties in NH3 data, IWAQM recommends use of the background levels 

provided above, unless better data are available for the specific modeling domain. IWAQM notes that 
141 

in areas where there are high ambient levels of sulfate, values such as 10 ppb might overestimate the 

formation of particulate nitrate from a given source, for these polluted conditions. IWAQM further 

notes that areas in the vicinity of strong point sources of NH3, such as feed lots or other agricultural 

areas, may experience locally high levels of background NH3. 

Questions regarding these recommendations should be resolved through consultation with the 

appropriate FLM and the appropriate State and/or EPA modeling representative. Applicants should 

provide a modeling protocol to the appropriate FLM prior to conducting modeling analyses. 

Estimation of Current and Future Deposition Rates 

In order to evaluate a proposed source’s contribution to total (wet + dry) deposition in a FLM area, it is 

necessary to first estimate current pollutant deposition rates. The current rate is a result of deposition 

from all existing natural and anthropogenic sources. FLMs use two approaches to estimating the 

current rate of deposition. One approach estimates the current rate by averaging data from an 

appropriate monitoring site for the pollutant of interest, using all years with complete data records. 

The second, more conservative, approach assumes that the current rate is equivalent to the highest rate 

for the pollutant of interest in the data record. 

The method for estimating future total deposition rates is: 

1. Identify in table D-2 available on-site or representative wet and dry deposition data for the FLM 

area. Wet deposition data can be obtained through NADP (http://nadp.sws.uiuc.edu/). 

Dry deposition data can be obtained through CASTNet at 

 http://www.epa.gov/castnet/

Table D-2 will indicate if dry deposition is assumed to equal wet deposition for the site. For highelevation sites, consult with the FLM to determine if deposition from cloudwater, fog, dew, or 

snowpack should be considered. For sites without on-site data, consult FLM for further guidance. 

2. After consulting with the FLM, estimate either: 

a. the average annual or seasonal wet and dry deposition rates for the appropriate pollutant 

using all years with complete data records; or 

b. the highest annual or seasonal wet and dry deposition rates for the appropriate pollutant 

using all years with complete data records. 

3. Calculate current total deposition (wet + dry = total). 

4. Estimate, using the appropriate dispersion model as described in the “Modeling Deposition Rates” 

section above, the proposed source’s contribution to future total deposition on an annual or 

seasonal basis. 

5. Estimate, using appropriate dispersion model as described in the “Modeling Deposition Rates” 

section above, the contribution of any sources permitted but not yet operating to future total 

deposition. This estimate may be available from the State permitting authority. 
142 

6. The current pollutant deposition rate plus the proposed source’s contribution to deposition plus 

the contribution from other sources permitted but not yet operating equals the future total 

deposition rate. 

 

Current + Proposed + Permitted (not yet operating) = Future Total Deposition 

This future total deposition rate for a given pollutant can then be used to determine the potential for 

adverse effects to AQRVs. If appropriate, the change in deposition rate can be used to estimate 

changes in pH or ANC in an ecosystem. If the future total deposition rate is expected to cause an 

adverse effect to AQRVs and/or exceeds the critical load established for a FLM area, the FLM may 

recommend mitigation, as outlined in the flowchart on Figure D-1. If no critical load has been 

established for the FLM area, the FLM will use the best information available in determining whether 

to recommend mitigation. 

g. Summary 

• Deposition of S and N has the potential to affect terrestrial, freshwater, and estuarine 

ecosystems on FLM lands. 

• The FLM has identified, where possible, AQRVs sensitive to deposition of S and N on FLM 

lands and the critical loads associated with those AQRVs. 

• A proponent of a source of new emissions with the potential to contribute to S or N deposition 

in an FLM area should consult with the FLM to determine what analyses are needed to assess 

AQRV effects. The FLM may request a deposition impact analysis, described in detail in this 

chapter and summarized below. 

1. Estimate the current deposition rate to the FLM area. A list of monitoring sites providing 

data to characterize deposition in FLM areas is included in Table D-2. 

2. Estimate the future deposition rate by adding the existing rate, the new emissions’ 

contribution to deposition, and the contribution of sources permitted but not yet operating. 

Modeling of new and permitted but not yet operating emissions’ contribution to deposition 

should be conducted following IWAQM Phase 2 recommendations. 

3. Compare the future deposition rate with the recommended screening criteria (e.g., critical 

load, concern threshold, or screening level value) for the affected FLM area. A list of 

documents summarizing these screening criteria, where available, can be found in 

Appendix H. Information for USDA/FS Class I areas is also available at: 

http://www.fs.fed.us/r6/aq/natarm. 

A web site with NPS and FWS Class I area information is currently under development. 

The web site will be available at 

http://www.nature.nps.gov/ard and http://refuges.fws.gov. 

The appropriate FLM should be contacted for additional information. 
143 

h. Websites for Deposition and Related Information 

Clean Air Status and Trends Network (CASTNet) dry deposition data: 

http://www.epa.gov/castnet/

IWAQM guidance for deposition modeling: http://www.epa.gov/scram001/7thconf/calpuff/phase2.pdf

National Acid Precipitation Assessment Program: No longer Available, CENR overseas AIRMoN Dry

http://www.arl.noaa.gov/research/projects/airmon_dry.html

National Atmospheric Deposition Program (NADP) wet deposition data: http://nadp.sws.uiuc.edu/

National Park Service Airweb: http://www.nature.nps.gov/ard/

Natural Resources Conservation Service, Snow Water Equivalent Information (SNOTEL): 

www.wcc.nrcs.usda.gov/factpub/sntlfct1.html

Southern Appalachian Man and the Biosphere Cooperative, Southern Appalachian Assessment: 

http://samab.org/


 

USDA Forest Service National Air Resource Management Web Site: 

http://www.fs.fed.us/r6/aq/natarm

U.S. EPA Office of Air and Radiation: 

http://www.epa.gov/oar

U.S. EPA, Deposition to Estuaries: 

http://www.epa.gov/owow/oceans/airdep

U.S. EPA, STOrage and RETrieval System for Water and Biological Monitoring Data (STORET): 

http://www.epa.gov/OWOW/STORET/

U.S. Fish and Wildlife Service Air Quality Branch: http://www.fws.gov/refuges/habitats/airQuality.html

U.S. Geological Survey, National Water-Quality Assessment (NAWQA) Program: 

http://water.usgs.gov/nawqa/

U.S. Geological Survey, Acid Rain Program: 

http://bqs.usgs.gov/acidrain

U.S. Geological Survey, Water Data Storage and Retrieval System (WATSTORE): 

http://h2o.er.usgs.gov/public/nawdex/wats/intro.html

Fact Sheet: http://water.usgs.gov/public/pubs/FS/FS-013-97/
144 

Table D-2. Sites used for estimating wet and dry deposition in Class I Areas (distance and direction, when noted, 

refer to the location of the monitoring site relative to the Class I area). 

ESTIMATION OF WET DEPOSITION – 

NADP 

ESTIMATION OF DRY DEPOSITION - 

CASTNet 

National Park 

Service Class I 

Units 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Acadia NP Y ME98 Y ACAD 

Arches NP N UT98 N dry = wet 

Badlands NP N SD08 N dry = wet 

Bandelier NM Y NM07 N dry = wet 

Big Bend NP Y TX04 Y BIBE 

Black Canyon of 

the Gunnison NP 

N CO08 N dry = wet 

Bryce Canyon NP Y UT99 N dry = wet 

Canyonlands NP Y UT98 Y CANY 

Capitol Reef NP N UT99 N dry = wet 

Carlsbad Caverns 

NP 

N TX22 N dry = wet 

Chiricahua NM Y AZ98 Y CHIR 

Crater Lake NP N OR09 N dry = wet 

Craters of the 

Moon NM 

Y ID03 N dry = wet 

Denali NP Y AK03 Y DENA 

Everglades NP Y FL11 Y EVER 

Glacier NP Y MT05 Y GLAC 

Grand Canyon NP Y AZ03 Y GRCA 

Grand Teton NP N WY08 N dry = wet 

Great Sand 

Dunes NM 

N CO00 N dry = wet 

Great Smoky 

Mountains NP 

Y TN11 Y GRSM Use background 

value N dep=17.4 

kg/ha/yr 

S dep=35.7 

kg/ha/yr 

(includes 

wet+dry+cloud/fog)

(SAMI) 

Guadalupe 

Mountains NP 

Y TX22 N dry = wet 

Haleakala NP N N/A N dry = wet 

Hawaii Volcanoes 

NP 

Y HI99 N dry = wet 

Isle Royale NP Y MI97 N dry = wet 

Joshua Tree NP Y CA67 Y JOTR 

Lassen Volcanic 

NP 

Y CA96 Y LAVO 

Lava Beds NM N CA76 N dry = wet 
145 

 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

National Park 

Service Class I 

Units 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Mammoth Cave 

NP 

N KY99 N dry = wet 

Mesa Verde NP Y CO99 Y MEVE 

Mount Rainier NP Y WA99 Y MORA 

North Cascades 

NP 

Y WA19 Y NOCA 

Olympic NP Y WA14 Y OLYM 

Petrified Forest 

NP 

N AZ03 N dry = wet 

Pinnacles NM Y CA66 Y PINN 

Point Reyes NS N N/A N dry = wet 

Redwood NP N N/A N dry = wet 

Rocky Mountain 

NP 

Y CO98/19 Y ROMO 

Saguaro NP N AZ99 N dry = wet 

Sequoia / Kings 

Canyon NPs 

Y CA75 Y SEKI 

Shenandoah NP Y VA28 Y SHEN 

Theodore 

Roosevelt NP 

Y ND07 Y THRO 

Virgin Islands NP Y VI01 Y VIIS 

Voyageurs NP Y MN23 Y VOYA 

Wind Cave NP N SD08 N dry = wet 

Yellowstone NP Y WY08 Y YELL 

Yosemite NP Y CA99 Y YOSE 

Zion NP N UT99 N dry = wet 

 

ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Forest Service 

Class I Areas 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Agua Tibia N N/A N N/A 

Alpine Lake N WA19/21 70 miles N/70 

mi SW 

N dry = wet 

Anaconda-Pintler N MT97 15 mi NE N dry = wet 

Ansel Adams N N/A N N/A 

Bob Marshall N MT05 65 mi NW N 468 GNP 65 mi NW 
146 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Forest Service 

Class I Areas 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Boundary Waters Y MN18/08 adjacent N dry = wet 

Bradwell Bay N FL14/* 30 mi N/ 

17 mi SW 

N 156 SUM 17 mi SW 

Bridger N WY06/ 

WY98 

6 mi SW/ 

4 mi W 

N 165 PND 6 mi W, bulk dep 

available 

Cabinet 

Mountains 

N MT05 85 mi E N dry = wet 

Caney Creek N AR03 60 mi SE N 150 CAD 60 mi SE 

Caribou N N/A N N/A 

Chiricahua N AZ99 92 mi NW Y 467 

CNM/167 

CNM 

adjacent 

Cohutta N TN11 N GRSM 

Cucamonga N N/A N N/A 

Desolation N N/A N N/A 

Diamond Peak N OR10 45 mi N N dry = wet 

Dolly Sods 

 

N WV18 17 mi W N 107 PAR 17 mi W 

Dome Land N N/A N N/A 

Eagle Cap 

 

N OR18 35 mi W N dry = wet 

Eagles Nest N CO02/94 40 mi NE N dry = wet 

Emigrant 

 

N N/A N N/A 

Fitzpatrick N WY06/ 

WY98 

13 mi SW/ 

17 mi W 

N 165 PND 13 mi W, bulk dep 

available 

Flat Tops 

 

N CO92/ 

CO08 

25 mi SW N dry = wet 

Galiuro N AZ99 40 mi N/NE N 467 

CNM/167 

CNM 

75 mi SE 

Gates of the 

Mountains 

N MT05 30 mi S N dry = wet 

Gearhart 

Mountain 

N OR9 45 mi N N dry = wet 

Gila Y NM01 adjacent N dry = wet 

Glacier Peak N WA19 10 mi NW N dry = wet 
147 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Forest Service 

Class I Areas

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Goat Rocks N WA21 40 mi NW N dry = wet 

Great Gulf N NH02/ME0

2 

30 mi SW/35 

mi SE 

N 109 WST 30 mi SW 

Hells Canyon N OR18/ID04 90 mi W/85 mi

NE 

N dry = wet 

Hercules-Glades N AR16/27 50 mi SE/90 

mi SW 

N dry = wet 

Hoover N N/A N N/A 

James River Face N VA13 65 mi W N 120 VPI 65 mi W 

Jarbidge N N/A N 164 SAV 50 mi SW 

John Muir N N/A N N/A 

Joyce-KilmerSlickrock 

N N/A N 137 COW 45 mi E 

Kaiser N N/A N N/A 

Kalmiopsis N N/A N dry = wet 

La Garita N CO91 30 mi S N dry = wet 

Linville Gorge N N/A N 126 PNF 15 mi N 

Lye Brook Y VT01/* 20 mi 

SW/adjacent 

Y 145 LYE adjacent 

Marble Mountain N N/A N N/A 

Maroon BellsSnowmass 

N * 3 mi S N 161 GTH 3 mi S 

Mazatzal N AZ03 142 mi N/NW N 474 

GCN/174 

GCN 

142 mi N/NW 

Mission 

Mountains 

N MT05 60 mi N N dry = wet 

Mokelumne N N/A N N/A 

Mount Adams N OR98 55 mi NE N 

Mount Baldy N AZ99 67 mi SW N dry = wet 

Mount Hood N OR98 20 mi NW N dry = wet 

Mount Jefferson N OR10 30 mi SW N dry = wet 

Mount 

Washington 

N OR10 15 mi SW N dry = wet 
148 

 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Forest Service 

Class I Areas 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Mountain Lakes N CA76/OR10 50 mi SW/125 

mi N 

N dry = wet 

North Absaroka N WY08 30 mi W N dry = wet 

Otter Creek N WV18 4 mi N N 107 PAR 4 mi N 

Pasayten N WA19 30 mi SW N dry = wet 

Pecos N NM07 38 mi SW N 405 MEV 163 mi NW 

Pine Mountain N AZ03 125 mi N N 474 

GCN/174 

GCN 

125 mi N 

Presidential 

Range-Dry River 

N NH02/ME02 25 mi SW/30 

mi SE 

N 109 WST 25 mi SW 

Rainbow Lake N WI37/36 45 mi SW/70 

mi E 

N 134 PRK 70 mi S 

Rawah N CO98/19 25 mi SW N 169 

CNT/406 

ROM 

30 mi NW/20 mi 

SE 

San Gabriel N N/A N N/A 

San Gorgonio N N/A N N/A 

San Jacinto N N/A N N/A 

San Pedro Parks N NM09 4 mi SW N 405 MEV 113 mi NW 

San Rafael N N/A N N/A 

Sawtooth N ID15/03 50 mi NW/80 

mi SE 

N dry = wet 

Scapegoat N MT05 100 mi NW N dry = wet 

Selway-Bitterroot N MT97 20 mi SE N dry = wet 

Shining Rock N N/A N 137 COW 20 mi W 

Sierra Ancha N AZ03 175 mi NW N 474 

GCN/174 

GCN 

175 mi NW 

Sipsey N N/A N dry = wet 

South Warner N AL99/10 80 mi E/140 

mi S 

N N/A 

Strawberry 

Mountain 

N OR18 75 mi N N dry = wet 

Superstition N AZ06 142 mi NW N dry = wet 
149 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Forest Service 

Class I Areas 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Sycamore Canyon N AZ06 79 mi N N 474 

GCN/174 

GCN 

79 mi N 

Teton N WY08/ 

WY98 

NW/SE N dry = wet 

Thousand Lakes N N/A N N/A 

Three Sisters N OR10 5 mi NW N dry = wet 

Upper Buffalo N AR16/27 60 mi NE/45 

mi NW 

N dry = wet 

Ventana N N/A N dry = wet 

Washakie N WY08/98 45 mi NW/60 

mi S 

N dry = wet 

Weminuche Y CO96/91 6 mi 

NW/adjacent

N 405 MEV 45 mi SW 

West Elk N * 20 mi NE N 161 GTH 20 mi NE 

Wheeler Peak N NM12 83 mi NE N 405 MEV 130 mi NW 

White Mountain N NM08 42 mi SE N dry = wet 

Yolla Bolly Middle 

Eel 

N N/A N N/A 

 ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

 Fish and Wildlife 

Class I Areas 

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Bering Sea N AK03 1100 km E N dry = wet 

Bosque del 

Apache 

N NM08 163 km SE N dry = wet 

Breton N LA30 175 km NW N dry = wet 

Brigantine Y NJ00 on-site N dry = wet 

Cape Romain starts 9/2000 SC18 87 km NW; 

use on-site 

data when 

available 

N dry = wet 

Chassahowitzka Y FL05 on-site N dry = wet 

Lostwood N MT13 130 km SW N dry = wet 
150 

ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

Fish and Wildlife 

Class I Areas

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

Medicine Lake N MT13 47 km W N dry = wet 

Mingo N MO05 1 km SW N dry = wet 

Moosehorn N ME98 107 km SW N dry = wet 

Okefenokee Y GA09 On-site N dry = wet 

Red Rock Lakes N WY08 106 km NE N dry = wet 

Salt Creek N NM08 120 km SW N dry = wet 

Seney starts 9/2000 MI98 98 km E; use 

on-site data 

when avail. 

N dry = wet 

Simeonof N AK03 1200 km NE N dry = wet 

St. Marks N FL23 50 km W N dry = wet 

Swanquarter N NC06 80 km S N dry = wet 

Tuxedni N AK03 450 km NE N dry = wet 

UL Bend N MT98 180 km NW N dry = wet 

Wichita Mountains N OK17 103 km NE N dry = wet 

Wolf Island N GA09 103 km SW N dry = wet 

ESTIMATION OF WET DEPOSITION – 

NADP

ESTIMATION OF DRY DEPOSITION - 

CASTNet

International 

Class I Areas

On-site 

monitoring 

Cal Code Comments On-site 

monitoring 

Site/ID Comments 

RooseveltCampobello 

N ME98 N dry = wet 

Distance and direction, when noted, refer to the location of the monitoring site relative to the Class I 

area. 

N/A is not available 

NADP data are available at http://nadp.sws.uiuc.edu

CASTNet data for NPS are available from john_ray@nps.gov

CASTNet data for USDA/FS are available at http://www.epa.gov/acidrain/castnet 

Wet deposition data at CASTNet site available from frank.neil@epa.gov
151 

E. FUTURE FLAG WORK 

1. IMPLEMENTING FLAG RECOMMENDATIONS 

FLAG participants believe that the recommendations in this document should be implemented as soon 

as possible. Therefore, an attempt has been made to present thorough and clear guidance of the 

processes that will be used to protect and improve AQRVs in FLM areas. 

Many of the issues and recommendations discussed herein are complex and require specialized 

knowledge. Consequently, State agencies and others who intend to use this information in NSR/PSD 

permitting, land planning and use, and other activities, deserve further guidance and implementation 

assistance. FLAG members anticipate that much of this guidance and assistance will be provided 

locally through established formal and informal links between FLMs, States, EPA and others. 

However, FLAG members also see the need to conduct workshops and training sessions and to 

provide guidance on the Internet. 

2. PHASE I UPDATES 

The FLAG Phase I report is intended to clearly state FLM guidance regarding NSR/PSD as it exists 

in December 2000. As the FLMs learn more about how to better assess the health and status of 

AQRVs, and as EPA produces new modeling tools, the FLAG guidance will be revised 

accordingly. As periodic revisions become necessary, any such revisions will be made to the webbased FLAG report. Any revisions to the report will be clearly stated on the FLAG web site. 

Additionally, once EPA promulgates the New Source Review Reform regulations, the FLMs may 

need to revise the FLAG Phase I report to address any inconsistencies that may result. 

3. PHASE II TASKS 

Phase I has addressed issues that could be resolved relatively quickly, without extensive research or 

the collection of new data. During Phase II, FLAG will address the more complex issues and concerns, 

including those that may require additional data collection. 

In Phase II, to the extent resources permit, FLAG members intend to fill information gaps identified in 

Phase I, recommend methods for establishing critical loads of pollutants, and attempt to resolve 

remaining differences in the policies and processes FLMs use to evaluate the effects of pollutants on 

AQRVs. In Phase II FLAG will also provide additional research and monitoring recommendations. 

Other potential Phase II tasks include: 

 Refine policies to prevent adverse AQRV impacts, and restore adversely impacted AQRVs. 

 Refine procedures for cumulative AQRV impact analyses. 

 Promoting internal (FLM) emission reductions through implementation of sustainable 

practices. 

 Recommending a policy on redesignation of Class II federal lands to Class I. 

 Clarifying FLM roles and responsibilities on Class II lands. 

 Recommending a consistent policy regarding increment tracking and enforcement. 

Issue-specific Phase II tasks are discussed in the individual subgroup reports. 
152 

APPENDIX A. GLOSSARY 

The list below contains definitions for some of the terms used in the FLAG Phase I Report. These 

terms are defined in the sense that they relate to the work of the Federal Land Managers (FLMs) in 

protecting air resources. 

For terms whose definition is lengthy or complex, the associated Code of Federal Regulations (CFR) 

section or other reference is cited. 

AIR QUALITY RELATED VALUE (AQRV). A resource, as identified by the FLM for one or 

more Federal areas, that may be adversely affected by a change in air quality. The resource may 

include visibility or a specific scenic, cultural, physical, biological, ecological, or recreational resource 

identified by the FLM for a particular area.

ADVERSE IMPACT ON AN AQRV. An unacceptable effect, as identified by an FLM, that results 

from current, or would result from predicted, deterioration of air quality in a Federal Class I or Class II 

area. A determination of unacceptable effect shall be made on a case-by-case basis for each area taking 

into account existing air quality conditions. It should be based on a demonstration that the current or 

predicted deterioration of air quality will cause or contribute to a diminishment of the area's national 

significance, impairment of the structure and functioning of the area's ecosystem, or impairment of the 

quality of the visitor experience in the area. 

ADVERSE IMPACT ON VISIBILITY. Visibility impairment which interferes with the 

management, protection, preservation, or enjoyment of a visitor's visual experience of a Federal Class 

I or Class II area. This determination must be made on a case-by-case basis taking into account the 

geographic extent, intensity, duration, frequency and time of visibility impairments, and how these 

factors correlate with (1) times of visitor use of the Class I area, and (2) the frequency and timing of 

natural conditions that reduce visibility. This term does not include effects on integral vistas. [40 CFR 

§51.301(a)] 

ABSORPTION. The process by which incident light is removed from the atmosphere and retained by 

a particle. 

ABSORPTION COEFFICIENT. A number that is proportional to the “amount” of light removed 

from a sight path by absorption per unit distance.

ACIDIFICATION. The decrease of acid neutralizing capacity in water or base saturation in soil 

caused by natural or anthropogenic processes. 

AEROSOL. A mixture of microscopic solid or liquid particles in a gaseous medium. Smoke, haze, 

and fog are aerosol examples. 

AIRSHED. A geographic area that, because of topography, meteorology, and/or climate, is frequently 

affected by the same air mass.

AOT40. Sum of all hourly average concentrations after subtracting 40 ppb from each hourly value. 
153 

BACT (BEST AVAILABLE CONTROL TECHNOLOGY). The control level (or control 

measures) required for sources subject to PSD. (See 40 CFR §52.21(b)(12), or 40 CFR 

§51.166(b)(12)). 

CLASS I AREA. As defined in the Clean Air Act, the following areas that were in existence as of 

August 7, 1977: national parks over 6,000 acres, national wilderness areas and national memorial 

parks over 5,000 acres, and international parks. 

CRITICAL LOAD. The concentration of air pollution above which a specific deleterious effect may 

occur. 

CUMULATIVE EFFECT. The impact on an AQRV resulting from the total pollutant loading from 

all sources including the contributing effects of known and reasonably foreseeable new and modified 

sources of air pollution. A single source may cause individually minor, but cumulatively significant, 

effects on AQRVs. 

DAMAGE. Any reduction in the intended use or value of a biological or physical resource. For 

example, economic production, ecological structure or function, aesthetic value, or biological or 

genetic diversity that may be altered by a pollutant. 

EMISSION OFFSET. A Federally enforceable reduction in emissions from an existing source that 

mitigates the impacts of a proposed new or modified source on AQRVs, PSD increments, and/or 

NAAQS. Also, Federally enforceable reductions in actual emissions from existing sources in a 

nonattainment area such that the total allowable emissions from a new or modified source and existing 

sources will be sufficiently less than the total emissions from existing sources before the application 

for a permit to construct so as to represent reasonable further progress towards attainment of the 

NAAQS. (See 42 U.S.C. § 7503(a)(1)(A)) 

EXTINCTION. The attenuation of light due to scattering and absorption as it passes through a 

medium. 

FUGITIVE EMISSIONS. Emissions which do not pass through a stack, chimney, vent, or other 

functionally equivalent opening. 

FEDERAL LAND MANAGER (FLM). The Secretary of the Department with authority over 

such lands. [40 CFR §51.166(b)(24)] The FLM for the Department of the Interior has been 

delegated to the Assistant Secretary for Fish and Wildlife and Parks; the FLM for the Department 

of Agriculture has been delegated to the Forest Service, and has been redelegated to the Regional 

Forester or individual Forest Supervisor. 

FLUX. Gaseous uptake into plant tissue. 

GREEN LINE. The total pollutant loading (contributions from existing and proposed sources) below 

which there is a very high degree of certainty that no AQRV will be adversely affected. 

HAZE. An atmospheric aerosol of sufficient concentration to be visible. The particles are so small 

that they cannot be seen individually, but are still effective attenuating light and reducing visual range. 
154 

HYDROCARBONS. Compounds containing only hydrogen and carbon. Examples: methane, 

benzene, and decane. 

HYGROSCOPIC. Readily absorbing moisture, as from the atmosphere. 

INJURY. Any physical or biological response to pollutants, such as a change in metabolism, reduced 

photosynthesis, leaf necrosis, premature leaf drop, or chlorosis. 

LAER (LOWEST ACHIEVABLE EMISSIONS RATE). The control level required of a source 

subject to nonattainment review. (See 40 CFR §51.165(a)(1)(xiii)) 

LIMIT OF ACCEPTABLE CHANGE. The amount of change that could occur without 

significantly altering an AQRV or sensitive receptor. 

MICROMETER. A unit of length equal to one millionth of a meter; the unit of measure for particle 

size. 

MIE THEORY. A complex mathematical model that allows the computation of the amount of energy 

(light) scattered by spherical particles. 

N100. Number of hourly average concentrations ≥100 ppb. 

NATURAL CONDITIONS. Conditions substantially unaltered by humans or human activities. As 

applied in the context of visibility, natural conditions include naturally occurring phenomena that 

reduce visibility as measured in terms of light extinction, visual range, contrast, or coloration. 

NATURAL VISIBILITY CONDITIONS. Visibility conditions attributable to Rayleigh scattering 

and aerosol associated with natural processes. 

NEPHELOMETER. An instrument that measures the amount of light scattered. 

NITRATES. Those gases and aerosols that have origins in the gas-to-aerosol conversion of nitrogen 

oxides, e.g., NO2 ; of primary interest are nitric acid and ammonium nitrate. Ammonium nitrate is very 

hygroscopic so its contribution to visibility impairment is magnified in the presence of water vapor. 

NITROGEN DIOXIDE. A gas (N02) consisting of one nitrogen and two oxygen atoms It absorbs 

blue light and therefore has a reddish-brown color associated with it. 

NONATTAINMENT AREA. An area designated by the EPA Administrator pursuant to Section 

107(d) of the Clean Air Act as having air quality which does not meet one or more National Ambient 

Air Quality Standard (NAAQS). For a list of nonattainment areas, see 40 CFR Part 81, Subpart C. 

OXIDANT STIPPLE. Small brown or black interveinal necrotic lesions on the adaxial surface of 

leaf tissue that can be attributed to exposure to ozone.

PHYTOTOXIC. Poisonous to plants. 

POST-CONSTRUCTION MONITORING. Monitoring required as a permit condition that the 

permitting authority considers necessary to determine the effect emissions from a stationary source 
155 

may have, or are having, on the air quality or on the AQRVs of an area. Such monitoring includes 

both “ambient” monitoring and “AQRV” monitoring and may involve short-term and long-term 

measurements made at locations representative of the greatest expected impacts. 

PSD INCREMENTS. The maximum increases in ambient pollution concentrations allowed over 

baselines concentrations. See 40 CFR §51.166 (c) for increments for specific pollutants. 

RACT (REASONABLY AVAILABLE CONTROL TECHNOLOGY). The lowest emissions 

limit that a particular source can meet by the application of control technology that is reasonably 

available considering technological and economic feasibility.

RAYLEIGH SCATTERING. The scattering of light by particles much smaller than the wavelength 

of the light, e.g., molecular scattering in the natural atmosphere. 

RECONSTRUCTED EXTINCTION. Extinction estimate that results from summing up the 

product of the mass of each measured particle species and the appropriate absorption or extinction 

coefficient. 

RED LINE. The total pollutant loading (contributions from existing and proposed sources) at which 

there is a very high degree of certainty that at least one AQRV will be adversely affected. 

REGIONAL HAZE VISIBILITY IMPAIRMENT. Any humanly perceptible change in visibility 

(light extinction, visual range, contrast, coloration) from that which would have existed under natural 

conditions, caused predominantly by a combination of many sources from, and occurring over, a wide 

geographic area. 

RE-OPENER. A permit condition that requires the permitting authority, at a specified time after 

permit issuance, to review and revise, if necessary, the permit based on new information such as the 

findings from post-construction monitoring, updated emissions inventories, updated modeling, 

research, or information on air pollution effects to terrestrial, aquatic, and visibility resources. 

SCATTERING. An interaction of a light with an object (e.g., a fine particle) that causes the light to 

be redirected in its path. 

SCATTERING COEFFICIENT. Measure of the ability of particles to scatter light; measured in 

number proportional to the “amount” of light scattered per unit distance. 

SCREENING LEVEL OR SCREENING LEVEL VALUE (SLV). The concentration or dose of 

air pollution below which estimated impacts from a proposed new or modified source are considered 

insignificant. The SLV is dependent on existing air quality and on the condition of the AQRV of 

concern. 

SENSITIVE RECEPTOR. The AQRV, or part thereof, that is the most responsive to, or the most 

easily affected by the type of air pollution in question. For example, at Great Smoky Mountains 

National Park, spruce-fir forest is a sensitive receptor of the AQRV flora. 

SENSITIVE RECEPTOR INDICATOR. A measurable physical, chemical, biological, or social 

(e.g., odor) characteristic of a sensitive receptor. For example, for the sensitive receptor, Crater Lake, 

water clarity is a sensitive receptor indicator. 
156 

STATIONARY SOURCE. A source of pollution that is well defined, such as the smokestack of a 

coal-fired power plant or smelter. 

SULFATES. Those aerosols that have origins in the gas-to-aerosol conversion of sulfur dioxide; of 

primary interest are sulfuric acid and ammonium sulfate. Sulfuric acid and ammonium sulfate are 

very hygroscopic so their contribution to visibility impairment is magnified in the presence of water 

vapor. 

SULFUR DIOXIDE. A gas (S02) consisting of one sulfur and two oxygen atoms. Of interest 

because sulfur dioxide converts to an aerosol. 

SUM00. The sum of all hourly average concentrations above 0 ppb. 

SUM06. The sum of all hourly average concentrations at or above 60 ppb. 

TARGET LOAD. The acceptable concentration or dose of an air pollutant that provides a reasonable 

margin of safety below the critical load. The target load should be achievable under existing 

conditions. 

TRANSMISSOMETER. An instrument that measures the amount of light extinction over a fixed, 

specified path length. 

VISIBILITY IMPAIRMENT. Any humanly perceptible change in visibility (visual range, contrast, 

coloration) from that which would have existed under natural conditions. [40 CFR §51.301(x)] 

VISUAL RANGE. The distance at which a large black object would just disappear from view. 

VOLATILE ORGANIC COMPOUND (VOC). Any compound of carbon, except those excluded 

by EPA, that participates in atmospheric photochemical reactions. (See 40 CFR §51.100(s))

W126. An ozone index that multiplies each specific concentration by a sigmoidal weighted function, 

then sums all values. Wi = 1/[1 + Me

-(A x Ci)] , where M and A are constants 4403 and 126 ppm-1, 

respectively, wi is the weighting factor for ci, and ci is concentration in ppm.
157 

APPENDIX B. 

LEGAL FRAMEWORK 

 FOR MANAGING AIR QUALITY AND AIR QUALITY EFFECTS 

ON FEDERAL LANDS 

Introduction 

The regulation of air pollution sources has clearly been delegated to EPA, and as applicable, the 

States. However, Federal Land Managers (FLMs) have the responsibility to protect the particular 

values of the lands over which they have jurisdiction, to the extent they have been delegated the 

authority, from the adverse impacts of activities inside and outside these areas. 

This Appendix sets out the basic legal authorities and responsibilities with which the FLMs 

comprising FLAG must comply, in addition to those authorities which they can utilize to protect 

AQRVs on public lands. 

For the purposes of this Appendix only, the term "public lands" is defined to include units of the 

National Park, National Wildlife Refuge, and National Forest Systems. 

I. AGENCY ORGANIC ACTS 

A. Department of the Interior: National Park Service (NPS): 

This Organic Act is very specific in that it mandates national park unit managers: 

[T]o conserve the scenery and the natural and historic objects and wild life therein and to provide 

for the enjoyment of the same in such manner and by such means as will leave them unimpaired for 

the enjoyment of future generations. 

16 U.S.C. §1(1997); and 

[T]he authorization of activities shall be construed and the protection, management, and administration 

of these areas shall be conducted in light of the high public value and integrity of the National Park 

System and shall not be exercised in derogation of the values and purposes for which these various 

areas have been established, except as may have been or shall be directly and specifically provided for 

by Congress. 

16 U.S.C. § 1a-1 (1997) 

B. Department of the Interior: Fish and Wildlife Service (FWS): 

With respect to National Wildlife Refuge System lands (Refuge System lands under the jurisdiction 

of the United States Fish and Wildlife Service (FWS), FWS managers are required to manage 

Refuge System lands so to: 

[E]nsure that the biological integrity, diversity, and environmental health of the System are 

maintained for the benefit of present and future generations of Americans. 
158 

16 U.S.C. §668dd(a)(4)(B)(1997) 

C. Department of Agriculture: Forest Service (Forest Service) 

National Forest System lands are defined as: 

[A]ll National Forests reserved or withdrawn from the public domain of the United States, all 

national forests acquired through purchase, exchange, donation, or other means, all national 

grasslands and land utilization projects...and all lands waters, and other interests administered by 

the Forest Service. 

16 U.S.C. §1609(a)(1997) 

The Forest Service's Organic Administration Act of 1897 directs the Secretary of Agriculture to: 

[M]ake provisions for the protection against destruction by fire and depredations upon the public 

forests and national forests... 

16 Sec. §551(1997) 

The National Forest units are managed consistent with Land and Resource Management Plans 

(LRMPs) under the provisions of the National Forest Management Act (NFMA). 16 §U.S.C. 1604 

(1997). Any measures addressing AQRVs on National Forest System lands will be implemented 

through, and be consistent with, the provisions of an applicable LRMP or its revision (16 U.S.C. 

§1604(i)). 

The Secretary of Agriculture is required by law to prepare a Renewable Resource Assessment by 

1979, and every 10 years thereafter. By law this Assessment is required to address: 

3. A description of Forest Service programs in research, cooperative programs and management of 

the National Forest System, their relationships, and the relationships of these programs and 

responsibilities to public and private activities; and 

5. An analysis of the potential effects of global climate change on the condition of renewable 

resources on the Forests and rangelands of the United States; and 

6. An analysis of the rural and urban forestry opportunities to mitigate the buildup of atmospheric 

carbon dioxide and reduce the risk of global climate change. 

16 U.S.C. §1601(a) (1997) 

In addition, the Secretary of Agriculture is required to prepare and transmit to the President, a 

Renewable Resource Program (the Program) every 5 years. This Program must include program 

recommendations which recognize the fundamental need to protect, and where appropriate, 

improve the quality of ... air resources. 16 U.S.C. §1602(5)(C). 

The Forest Service's implementing regulations for NFMA are found at 36 C.F.R. §219 et seq. 

LRMPs are, in part, specifically based on: 
159 

[R]ecognition that the National Forests are ecosystems and their management for goods and 

services requires an awareness and consideration of the interrelationships among plants, animals, 

soil, water, air, and other environmental factors within such ecosystems. 

36 C.F.R. §219.1(b)(3) 

II. The Wilderness Act. 16 U.S.C. §1131 (1997). 

AQRVs in Wilderness areas may receive further protection by the language of the Wilderness Act 

itself which states: 

Wilderness areas... shall be administered for the use of the American people in such a manner as 

will leave them unimpaired for future use and enjoyment as wilderness .... (16 U.S.C. Sec. §1131). 

For Wilderness Areas in the National Forest System, the Act's implementing regulations are found 

at 36 C.F.R. §293. These Wilderness Areas shall be administered: 

...[For] such other purposes for which it may have been established in such a manner as to preserve 

and protect [their] wilderness character. In carrying out such purposes, National Forest Wilderness 

resources shall be managed to promote, perpetuate, and, where necessary, restore the wilderness 

character of the land... 

36 C.F.R. §293.2 (1997) 

III. The Clean Air Act, 42 U.S.C. §7401 et seq. 

Because of a perceived need for national and regional air quality research to support State 

programs, Congress passed its first federal air quality initiative in 1955. (Air Pollution Control Act 

of 1955, ch. 360, 69 Stat. 322). In response to increasing harm to public health and welfare and to 

inadequate controls and enforcement, Congress has slowly but steadily expanded and refined the 

law, now known as the Clean Air Act (CAA), to cover more types of pollutants and emitters; e.g., 

stationary and mobile sources of pollution. These efforts have culminated in the 1990 Amendments 

to the CAA, which represent the most comprehensive and detailed set of measures to date to both 

prevent and curtail air pollution. 

The declaration of purpose, as revised in 1990 states in part: 

The purposes of this subchapter are: to protect and enhance the quality of the Nation’s air resources so 

as to promote the public health and welfare and the productive capacity of its population. 

42 U.S.C. § 7401(b)(1); and 

A primary goal of this Act is to encourage or otherwise promote reasonable Federal, State, and 

local government actions, consistent with the provisions of this Act, for pollution prevention. 

42 U.S.C. §7401(c) 
160 

The CAA provides an additional legal framework for FLMs to preserve and protect AQRVs from 

pollution sources emanating both within and outside National Park, Forest, and Refuge boundaries. 

A. National Ambient Air Quality Standards (NAAQS) and State Implementation Plans 

(SIPs): The CAA establishes a regulatory program with the goal of achieving and maintaining 

"national ambient air quality standards" (NAAQS) through state or, if necessary, federal 

implementation plans (SIPs or FIPs).1 

The U.S. Environmental Protection Agency (EPA) is charged with promulgating: 

1. "primary" NAAQS for "criteria" pollutants "to protect the public health," allowing an adequate 

margin of safety;" and 

2. "secondary" NAAQS "to protect the public welfare from any known or anticipated adverse 

effects associated with the presence of such air pollutant in the ambient air."2 

The above secondary standards may help protect public land AQRVs.3

 To date, EPA has 

promulgated NAAQS for six criteria pollutants: sulfur dioxide, particulate matter, nitrogen dioxide, 

carbon monoxide, ozone and lead. In July of 1997, EPA issued revised, and more stringent 

NAAQS for ozone and "fine particulate matter" to address human health concerns. However, EPA 

openly acknowledged that these revised NAAQS were not fully adequate to protect the above 

"secondary" values, in particular those sensitive AQRVs on public lands. 

B. Prevention of Significant Deterioration (PSD): 

The CAA, as amended in 1977, includes the following major purposes regarding the "prevention of 

significant deterioration" (PSD) provisions: 

[T]o protect public health and welfare from any actual or potential adverse effect . . . from air pollution 

. . . notwithstanding attainment and maintenance of all national ambient air quality standards. 

42 U.S.C. § 7470(1) 

[T]o preserve, protect, and enhance the air quality in national parks, national wilderness areas, 

national monuments, national seashores, and other areas of special national or regional natural, 

recreational, scenic, or historic value. 

42 U.S.C. §7470(2) 

The PSD section provides some protection for park and wilderness AQRVs through establishment 

of ceilings on additional amounts of air pollution over baseline levels in clean air areas 

(increments). It requires EPA or the State to provide to the FLM notice of any proposed major 

emitting facility4

 whose emissions may affect a Class I area (42 U.S.C. §7475(d)(2)(A), and also by 

charging: 

[T]he Federal Land Manager 1

 and the Federal official charged with direct responsibility for 

management of such lands with "an affirmative responsibility to protect the air quality related 

values (including visibility) of any such lands within a class I area and to consider, in consultation 
161 

with the Administrator, whether a proposed major emitting facility will have an adverse impact on 

such values. 

42 U.S.C. §7475(d)(2)(B). 

Class I areas include national parks larger than 6,000 acres and national wilderness areas and 

national memorial parks which exceed 5,000 acres, in existence on August 7, 1977. The 1990 

Amendments provided that subsequent additions to the boundaries of such areas are also Class I 

areas. Currently, 48 areas in the National Park system, 21 Refuge System units, and 88 areas under 

the administration of the Forest Service are designated as Class I. 

Under the PSD provisions and implementing regulations (40 C.F.R. §51.166(p)), for Class I areas, 

once baseline concentrations come under review by submission of a PSD preconstruction permit 

application for a major new or modified emissions source, only the smallest increment of certain 

pollutants -- sulfur dioxide, nitrogen oxide and particulate matter -- may be added to the air by the 

proposed new source, and other "increment consuming" sources. 

Under the PSD provisions a FLM has several tools he/she may use to protect AQRVs. 

A state may not issue a PSD permit to allow construction or modification of a major emitting 

facility when the applicable Federal Land Manager files a notice alleging the facility may cause or 

contribute to a change in the Class I area's air quality and by identifying the potential adverse 

impact of such a change, unless: 

The facility owner demonstrates that the facility's emissions of particulate matter, sulfur dioxide, 

and nitrogen oxides will not cause or contribute to concentrations which will exceed the maximum 

allowable increases for that Class I area. 

42 U.S.C. §7475(d)(2)(C)(i)(paraphrased) and 42 U.S.C. §7476. 

Even if no increment violation is predicted, 

[T]he state may not issue a PSD permit, if the Federal Land Manager demonstrates to the 

satisfaction of the State that the emissions from such facility will have an adverse impact on the air 

quality-related values (including visibility) of Class I lands. 

42 U.S.C. §7475(d)(2)(C)(ii)(paraphrased) 

Neither the CAA nor the implementing regulations specify criteria for the FLM to "satisfy" state 

permitting agencies. Consequently, some states have taken a liberal view of their discretion to 

reject an FLM's adverse impact determination. However, EPA's Environmental Appeals Board 

(the Board) has ruled that state discretion in rejecting a FLM's finding of adverse impacts is not 

"unfettered" (see the Board's decisions regarding the permit appeals for the Old Dominion Electric 

Cooperative and Hadson Power projects in Virginia). Nevertheless, the appropriate role of the FLM 

in the PSD permit process is currently being addressed in EPA's proposed New Source Review 

Reform regulations. The final regulations are expected to be promulgated in 2001. 
162 

C. Visibility Protection. Subpart II, 42 U.S.C. §7491 et seq. (1997) 

The Visibility portion of the CAA: 

"... [D]eclares as a national goal the prevention of any future, and the remedying of any existing, 

impairment of visibility in mandatory class I Federal areas which impairment results from 

manmade air pollution." 

42 U.S.C. §7491(a)(1). 

To help carry out this goal, the Secretaries of the Interior and Agriculture are charged with 

identifying Class I areas where visibility is an important value. EPA is charged with reporting to 

Congress on methods to implement the national goal and with promulgating regulations to ensure 

reasonable progress toward meeting the goal. 

In 1980, EPA issued enforceable regulations for visibility impairment “reasonably attributable” to a 

specific source or small group of sources. In particular, major stationary sources emitting any 

pollutant which may “reasonably be anticipated to cause or contribute to any impairment of visibility” 

is required to install best available retrofit technology (BART). In addition, in April 1999 EPA 

promulgated final regulations addressing regional haze. The regional haze rule protects air quality in 

Class I areas by requiring States to plan to achieve “natural” visibility conditions over a 60-year 

timeframe. 

The 1990 Amendments add a new section on visibility, which authorizes EPA in conjunction with 

NPS and other federal agencies, to conduct visibility research and to evaluate clean air corridors 

and emissions sources and source regions causing visibility impairment in Class I areas. In this 

regard, EPA was required to establish the Grand Canyon Visibility Transport Commission 

(GCVTC) by 1991 and consider the recommendations GCVTC would make (42 U.S.C. §7492(f). 

NPS, FS, FWS, and BLM played a vital role in the work of the GCVTC and committees in an 

effort to improve air quality in the Grand Canyon and other parks and wilderness areas in the 

"Golden Circle" on the Colorado Plateau. 

As part of the visibility protection process, states are required to promulgate a plan to prevent any 

future, and remedy any existing impairment of visibility in Class I areas... 40 C.F.R. §51.300 

(1997). EPA has defined "visibility impairment" as: 

[A]ny humanly perceptible change in visibility (visual range, contrast, coloration) from that which 

would have existed under natural conditions. 

40 C.F.R. §51.301(x)(1997).7 

However, EPA has promulgated its visibility regulations to allow FLMs to use their existing 

authorities to address "visibility impairment" (rather than "significant impairment") so that "the 

affected Federal Land Manager may certify to the State, at any time, that there exists impairment of 

visibility in any mandatory Class I Federal area." 40 C.F.R. §51.302(c). 
163 

D. Nonattainment Areas, 42 U.S.C. §7501 et seq.: 

Areas that have failed to meet NAAQS for one or more criteria pollutants are designated as 

"nonattainment" areas. Under the 1990 Amendments, Congress provides for further classification 

of nonattainment areas based on severity of the nonattainment and availability and feasibility of 

appropriate pollution control measures and for a compliance schedule ranging from 1993 in 

marginal nonattainment areas to 2010 for Los Angeles. 

The 1990 Amendments authorize EPA to issue control technique guidance documents (CTGs) 

covering a variety of topics, such as control of idling vehicles and voluntary removal of pre-1980 

model year light duty vehicles (cash for clunker programs). (42 U.S.C. §7408.) EPA is authorized 

to issue CTGs, in lieu of regulations, to reduce "volatile organic compounds" (VOC) emissions 

from any consumer or commercial product. (42 U.S.C. §7511b.) 

Proposed new or modified major stationary sources within nonattainment areas are required to 

meet emissions limits based on "lowest achievable emission reduction" technology (LAER) and 

may be constructed only if their emissions are sufficiently offset by reductions in emissions from 

other sources. The 1990 Amendments also require analysis of alternative sites, sizes, production 

processes, and control techniques and a finding that the benefits of the source outweigh its 

environmental and social costs. (42 U.S.C. §7501-15.) 

E. General 

CAA Subchapter III 42 U.S.C. §7601 et seq. contains definitions, requirements for reports to 

Congress, authorizations for appropriations, and procedures for EPA rulemaking and judicial 

review. Citizen suits are authorized: 1) against EPA for failure to perform a nondiscretionary duty 

under the CAA, or 2) against others for alleged violations of an emission limitation, standard, or 

order. (42 U.S.C.§7601 et seq.) 

F. Acid Deposition 

The 1990 Amendments add Title IV, which contains requirements for electric utilities to reduce 

emissions associated with acid rain. To reduce the adverse effects of acid deposition, Title IV 

requires a reduction in annual emissions of sulfur dioxide of ten million tons from 1980 emission 

levels and a reduction of nitrogen oxides emissions of approximately two million tons from 1980 

emission levels, in the 48 contiguous states and the District of Columbia. (42 U.S.C. §7651.) The 

Title creates a system of market-based emission allowances, which can be traded among sources. 

See (42 U.S.C. §7651a-o.) 

G. Operating Permits 

The 1990 Amendments add Subchapter V, 42 U.S.C. §7661 et seq., which establishes a nationwide permit program for existing stationary sources. Permit requirements will include emission 

limitations. EPA may veto state permits, which do not comply with provisions of the CAA. (42 

U.S.C. §7661a-f.) 
164 

H. Conformity, 42 U.S.C. §7506 (1997) 

(Paraphrased) No federal agency may engage in, support in any way,... license or permit, or 

otherwise approve any activity which does not conform to an approved state (or federal) 

implementation plan. Conformity shall be an affirmative responsibility of the head of each agency. 

Conformity means: 

(A) Conforming to the SIP's purpose of eliminating or reducing the number of NAAQS violations; 

(B) That any such activities will not: 

(i) Cause or contribute to new violations in any area; or 

(ii) Increase the frequency or severity of any existing standard violation... 

EPA, in its "criteria and procedures" for implementing "conformity" has decided that only those 

activities that "a federal agency can practicably control, and will maintain control over due to a 

continuing program responsibility" are subject to same. 40 C.F.R. §93.152. 

Although required to comply with the conformity provisions (42 U.S.C. §7618(1997)), the FLM 

cannot use these provisions to protect AQRVs from adverse impacts from offsite sources. 

IV. IMPACT ON FEDERAL LAND MANAGERS 

The CAA reinforces the FLMs' Organic Act and Wilderness Act roles as protectors of AQRVs on 

public lands. 

The CAA also imposes on FLMs an obligation to comply with the Act's many provisions regarding 

the abatement of air pollution to the same extent as any private person (42 U.S.C. §7418). 

Thus, under various authorities, FLMs are responsible for protecting AQRVs within their 

respective unit boundaries and taking appropriate action to do so, when reviewing emission sources 

both within units, and in proximity to unit boundaries. 

FLMs, under the CAA, have an affirmative responsibility for protecting AQRVs (including 

visibility) in reviewing proposed PSD permits. However, because of the uncertainty involved in 

"satisfying" State permitting agencies in the PSD process, and the appropriate delegated role for 

FLMs in non-PSD situations, the existing framework may provide an inadequate means for FLMs 

to protect AQRVs from adverse impacts caused by sources outside unit boundaries. 
165 

References

1) Clean Air Act, 42 U.S.C. §7401-7671q (as amended 1990). 

2) Clean Air Deskbook, The Environmental Law Reporter, Environmental Law Institute, 1992. 

3) Managing National Park System Resources: A Handbook on Legal Duties, Opportunities, and 

Tools, Chap. 4 "The Clean Air Act" by Molly Ross at pp. 51-65, The Conservation Foundation, 

1990. 

4) Atmospheric Environment Vol. 27B, No. 1, "The 20-Year History of the Evolution of Air 

Pollution Control Legislation in the U.S.A." by Richard H. Schulze at pp. 15-25. 

5) Wilderness Act of 1964, 16 U.S.C. §1131 et seq, P.L. 577, 78 stat 890 as amended. 

6) The Principal Laws Relating to Forest Service Activities, USDA - Forest Service ISBN 0-16-

041927-1, 1993 

7) Organic Administration Act of 1897, 16 U.S.C. §473-475, §477-482, §551. 
166 

APPENDIX C. 

GENERAL POLICY FOR MANAGING AIR QUALITY 

RELATED VALUES IN CLASS I AREAS 

Most Federal Land Manager (FLM) enabling legislation and regulations developed to implement 

Federal Laws do not directly address air quality, or air pollution effects on Parks or Wildernesses. 

They do, however, provide broad direction on what should be protected in Parks and Wildernesses 

(the earth and its community of life) and to what degree (preserve natural conditions or conserve 

resources unimpaired). Accordingly, FLMs have developed the following policies related to air 

quality and Class I areas: 

1. Class I areas are not merely a commodity for human use and consumption. Park and Wilderness 

ecosystems have intrinsic values other than user/public concerns. 

2. A principle objective of FLM management is to offer a natural user experience, rather than 

strictly an enjoyable one. The amount of enjoyment is purely a personal matter for the 

individual user to decide. 

3. All Class I components are equally important; none is of lesser value than another. 

4. A Class I component is important even if users of the area are unaware of its existence. 

5. All life forms are equally important. For example, microorganisms are as essential as elk, wild 

flowers, or grizzly bears. 

6. The goal of Class I management is to protect not only resources with immediate aesthetic 

appeal (i.e., sparkling clean streams) but also unseen ecological processes (such as natural 

biodiversity and gene pools). 

7. The most sensitive Class I components are to be emphasized more than those of “average” or 

“normal” sensitivity. Sensitivity is generally determined by inertia (resistance to change), 

elasticity (how far the component can be stretched from its natural condition without being 

permanently modified), and resiliency (the number of times it can revert to its natural condition 

after experiencing human-caused change). 

8. Each Class I component is important in itself; as well as in terms of how it interacts with other 

components of the ecosystem. That is, the individual parts of the Class I ecosystem are as 

significant as the sum of the parts. 

9. The physical components of the ecosystem (for instance, lake chemistry) are as essential as its 

biological constituents (i.e., salamanders). That is, the earth is as essential as the community of 

life. 
167 

10. Class I components are to be protected from “human-caused change” rather than from 

“damage.” Terms such as “damage” and “harm” are prejudicial, whereas “human-caused 

change” is value-neutral. (For example, deposits of nitrogen in a lake from nitrogen oxide, a 

common air pollutant, might result in more plant growth and larger fish. This would, however, 

be an unnatural - and therefore unacceptable - change in the aquatic ecosystem). 

11. The goal of Class I management is to protect natural conditions, rather than the conditions 

when first monitored. That is, if initial monitoring in a Class I area identifies human-caused 

changes, appropriate actions should be taken to remedy them, in order to move towards a more 

natural condition. 

12. The designation of a Park or Wilderness as Class I or II does not dictate the management goals 

for it; these are identified in the enabling legislation. The designation only determines which 

options are available to meet the goals. Class I Parks or Wildernesses, for instance, can be 

protected through AQRV analysis, whereas the protection of Class II Parks and Wildernesses 

can be achieved using BACT requirements. 

13. While it may not be possible to manage every Class I area in a natural or near-natural state, 

each should be managed in as pristine a condition as the specific (local) biophysical, legal, 

scientific, and social/political situation will allow. That is, FLMs will do the best job possible of 

Park and Wilderness management, based on local constraints and opportunities. The extent of 

actual protection, therefore, may vary. 

14. Although monitoring is critical to many air resource management decisions, it must not 

interfere needlessly with Park or Wilderness. Where possible, the most intrusive monitoring 

and instrumentation should be conducted adjacent to the Class I area - if such areas adequately 

represent the area of concern.
168 

APPENDIX D. 

BEST AVAILABLE CONTROL TECHNOLOGY (BACT) ANALYSIS

Given the need to minimize emissions and their resulting air quality impacts, the FLMs recommend 

that the applicant conduct the BACT analysis using EPA’s top-down approach. In brief, a topdown process ranks all available control technologies in descending order of control effectiveness. 

All of the available control systems for the source, including the most stringent, must be 

considered. The applicant first examines the most effective, or top, alternative. That alternative is 

established as the BACT unless the applicant demonstrates, and the permitting authority agrees, 

that technical considerations, or energy, environmental, or economic impacts justify a conclusion 

that the most stringent technology is not achievable in that case. FLMs utilize EPA’s 

BACT/RACT/LAER Clearinghouse, and other information, for assessing control technologies 

proposed by permit applicants. 

If the most stringent technology is eliminated in this fashion, then the next most stringent 

alternative is considered, and so on. Permit applicants should refer to chapter B of the EPA New 

Source Review Workshop Manual for a detailed discussion of the top-down policy. 

The FLM reviews the applicant's BACT analysis to determine if the best available pollution control 

technology is being proposed, thereby minimizing the proposed emission increases and their 

corresponding impact on the FLM area in question. The FLM does this by comparing the proposed 

controls to recent BACT determinations for similar facilities. If the FLM disagrees with the 

applicant's BACT analysis, technical comments are submitted to the permitting authority who has 

the ultimate responsibility to make the BACT determination and issue the permit. 

The environmental impacts analysis of the BACT review is not to be confused with the air qualityrelated analysis. The environmental impacts analysis of the BACT review should concentrate on 

impacts other than ambient air quality impacts of the regulated pollutant in question, such as solid 

or hazardous waste generation, discharges of polluted water from a control device, or emissions of 

unregulated pollutants. Thus, the fact that a given control alternative would result in only a slight 

improvement in ambient concentrations of the pollutant in question when compared with a less 

stringent control alternative, should not be viewed as a basis for rejecting the more stringent control 

alternative. 

Regarding the economic impact analysis, given the special protection Class I areas are afforded under 

the Clean Air Act, FLMs believe that the need to minimize potential impacts on a Class I area should 

be a major consideration in the BACT determination for a project proposed near such an area. 

Therefore, if a source proposes to locate near a Class I area, additional costs to minimize impacts on 

sensitive Class I resources may be warranted, even though such costs may be considered economically 

unjustified under other circumstances. 
169 

APPENDIX E. MAPS OF FEDERAL CLASS I AREAS 
170 

NATIONAL PARK SERVICE CLASS I AREAS 

Voyageurs 

\ 

Roosevelt NP 

ar s bad Caverns NP 

\ Guadalupe Mountains NP 

ALASKA NP 

\ 

'" (';;J and 

-oZJ. l.y.A ) ;p 

. 

Map p rod uced by the National Park Service Air Resources Division 02/22/ 1999 

HAWAII 

. 

t::::::;; 

Haleakala NP 

e 

Volcano
171 

FISH AND WILDUFE SERVICE CLASS I AREAS 

e

Wichita MounjPts 

•s t Creek 1 

"0 HAWAII 

.... -

\)<i:> "' 

prod uced by t h e Fish and 

Wild life Service Air Quality Branch 2/27/1998 

\) 
172 

FOREST SERVICE CLASS I WILDERNESS AREAS 

ass 

HAWAII 

. _,...

'· 

Map produced by the National Park Service Air Resources Division 08/ 2 3/1999 
173 

APPENDIX F. CLASS I AREA CONTACTS 

USDA FOREST SERVICE CLASS I AREAS 

REGION 1

Class I Areas: 

 Anaconda-Pintler Wilderness 

 Bob Marshall Wilderness 

 Cabinet Mountains Wilderness 

 Gates of the Mountains Wilderness 

 Mission Mountains Wilderness 

 Scapegoat Wilderness 

 Selway-Bitterroot Wilderness 

 

Contact: Ann Acheson 

 Phone Number: (406) 329-3493 

 Fax Number: (406) 329-3132 

 Email Address: aacheson@fs.fed.us 

 Mailing Address: 

 USDA Forest Service, Region 1 

 P.O. Box 7669 

 Missoula, MT 59807 

REGION 2

Class I Areas: 

 Eagles Nest Wilderness 

 Fitzpatrick Wilderness 

 Flat Tops Wilderness 

 La Garita Wilderness 

 Maroon Bells - Snowmass Wilderness 

 Mount Zirkel Wilderness 

 North Absaroka Wilderness 

 Rawah Wilderness 

 Washakie Wilderness 

 Weminuche Wilderness 

 West Elk Wilderness 

Contact: Dennis Haddow 

 Phone Number: (303) 275-5759 

 Fax Number: (303) 275-5754 

 Email Address: dhaddow@fs.fed.us 

 Mailing Address: 

 USDA Forest Service, Region 2 

 P.O. Box 25127 

 Lakewood, CO 80225-0127 
174 

REGION 3

Class I Areas: 

 Chiricahua Wilderness 

 Galiuro Wilderness 

 Gila Wilderness 

 Mazatzal Wilderness 

 Mount Baldy Wilderness 

 Pecos Wilderness 

 Pine Mountain Wilderness 

 San Pedro Parks Wilderness 

 Sierra Ancha Wilderness 

 Superstition Wilderness 

 Sycamore Canyon Wilderness 

 Wheeler Peak Wilderness 

 White Mountain Wilderness

Contact: Debby Potter, Ph.D. 

 Phone Number: (505) 842-3143 

 Fax Number: (505) 842-3800 

 Email Address: dapotter@fs.fed.us 

 Mailing Address: 

 USDA Forest Service, Southwestern Region 

 Federal Building 

 517 Gold Ave., S.W. 

 Albuquerque, NM 87102 

REGION 4

Class I Areas: 

 Bridger Wilderness 

 Hells Canyon Wilderness* 

 Hoover Wilderness 

 Jarbidge Wilderness 

 Sawtooth Wilderness* 

 Teton Wilderness

Contact: Dennis Haddow *Contact: Ann Acheson 

 Phone Number: (303) 275-5759 Phone Number: (406) 329-3493 

 Fax Number: (303) 275-5754 Fax Number: (406) 329-3132 

 Email Address: dhaddow@fs.fed.us Email Address: aacheson@fs.fed.us 

 Mailing Address: Mailing Address: 

 USDA Forest Service, Region 2 USDA Forest Service, Region 1 

 P.O. Box 25127 P.O. Box 7669 

 Lakewood, CO 80225-0127 Missoula, MT 59807 

 

 

 

 
175 

REGION 5

Class I Areas: 

 Caribou Wilderness 

 Marble Mountain Wilderness 

 South Warner Wilderness 

 Thousand Lakes Wilderness 

 Yolla Bolly - Middle Eel Wilderness 

Contact: Suraj Ahuja 

 Phone Number: (916) 934-5630 

 Fax Number: (916) 934-7384 

 Email Address: sahuja@fs.fed.us 

 Mailing Address: 

 Mendocino National Forest 

 420 E. Laurel Street 

 Willows, CA 95988 

Class I Areas: 

 Agua Tibia Wilderness 

 Cucamonga Wilderness 

 San Gabriel Wilderness 

 San Gorgonio Wilderness 

 San Jacinto Wilderness 

 San Rafael Wilderness 

 Ventana Wilderness 

 

 Contact: Mike McCorison 

 Phone Number: (818) 574-5286 

 Fax Number: (818) 574-5233 

 Email Address: mmccorison@fs.fed.us 

 Mailing Address: 

 Angeles National Forest 

 701 N. Santa Anita Ave. 

 Arcadia, CA 91006 
176 

Class I Areas: 

 Ansel Adams Wilderness 

 Desolation Wilderness 

 Dome Land Wilderness 

 Emigrant Wilderness 

 John Muir Wilderness 

 Kaiser Wilderness 

 Mokelumne Wilderness 

Contact: Trent Procter 

 Phone Number: (559) 784 -1500, ext. 1114 

 Fax Number: (559) 781 - 4744 

 Email Address: tprocter@fs.fed.us 

 Mailing Address: 

 Sequoia National Forest 

 900 W. Grand Ave. 

 Porterville, CA 93257-2035 

REGION 6

Class I Areas: 

 Alpine Lakes Wilderness 

 Diamond Peak Wilderness 

 Eagle Cap Wilderness 

 Gearhart Mountain Wilderness 

 Glacier Peak Wilderness 

 Goat Rocks Wilderness 

 Hells Canyon Wilderness 

 Kalmiopsis Wilderness 

 Mt. Adams Wilderness 

 Mt. Hood Wilderness 

 Mt. Jefferson Wilderness 

 Mt. Washington Wilderness 

 Mountain Lakes Wilderness 

 Pasayten Wilderness 

 Strawberry Mountain Wilderness 

 Three Sisters Wilderness 

Contact: Bob Bachman 

 Phone Number: (503) 808 - 2918 

 Fax Number: (503) 808 - 2973 

 Email Address: rbachman@fs.fed.us 

 Mailing Address: 

 USDA Forest Service, Region 6 

 P.O. Box 3623 

 Portland, OR 97208-3623 
177 

REGION 8

Class I Areas: 

 Dolly Sods Wilderness 

 James River Face Wilderness 

 Otter Creek Wilderness 

Contact: Cindy Huber 

 Phone Number: (540) 265-5156 

 Fax Number: (540) 265-5145 

 Email Address: chuber@fs.fed.us 

 Mailing Address: 

 Jefferson National Forest 

 5162 Valleypointe Parkway 

 Roanoke, VA 24019 

Class I Areas: 

 Joyce Kilmer - Slickrock Wilderness 

 Linville Gorge Wilderness 

 Shining Rock Wilderness 

Contact: Bill Jackson 

 Phone Number: (704) 257-4815 

 Fax Number: (704) 257-4263 

 Email Address: bjackson02@fs.fed.us 

 Mailing Address: 

 National Forests in North Carolina 

 P.O. Box 2750 

 Asheville, NC 28802 

Class I Areas: 

 Caney Creek Wilderness 

 Upper Buffalo Wilderness

Contact: Laura Hudnell 

 Phone Number: (501) 321-5235 

 Fax Number: (501) 321-5353 

 Email Address: lhudnell@fs.fed.us 

 Mailing Address: 

 Ouachita National Forest 

 Box 1270, Federal Building 

 Hot Springs Natl. Park, AR 71902 
178 

Class I Areas: 

 Bradwell Bay Wilderness 

 Cohutta Wilderness 

 Sipsey Wilderness 

Contact: Dave Wergowske 

 Phone Number: (334) 241-8137 

 Fax Number: (334) 241-8111 

 Email Address: dwergowske@fs.fed.us 

 Mailing Address: 

 National Forests in Alabama 

 2946 Chestnut Street 

 Montgomery, AL 36107-3010 

REGION 9

Class I Area: 

 Boundary Waters Canoe Area 

Contact: Robert Berrisford 

 Phone Number: (218) 720-5385 

 Fax Number: (218) 720-5600 

 Email Address: bberrisford@fs.fed.us 

 Mailing Address: 

 Superior National Forest 

 Box 338, Federal Building 

 515 W. First St. 

 Duluth, MN 55802 

Class I Area: 

 Lye Brook Wilderness 

Contact: Nancy Burt 

 Phone Number: (802) 747-6742 

 Fax Number: (802) 747-6766 

 Email Address: nburt@fs.fed.us 

 Mailing Address: 

 Green Mountain National Forest 

 231 N. Main Street 

 Rutland, VT 05701 
179 

Class I Areas: 

 Great Gulf Wilderness 

 Presidential Range - Dry River Wilderness 

Contact: Joan Carlson 

 Phone Number: (603) 528-8721 

 Fax Number: (603) 528-8783 

 Email Address: jcarlson@fs.fed.us 

 Mailing Address: 

 White Mountain National Forest 

 719 Main Street 

 Laconia, NH 03246-0772 

Class I Area: 

 Hercules - Glades Wilderness 

Contact: Laura Hudnell 

 Phone Number: (501)321-5235 

 Fax Number: (501) 321-5353 

 Email Address: lhudnell@fs.fed.us 

 Mailing Address: 

 Mark Twain National Forest 

 401 Fairgrounds Road 

 Rolla, MO 65401 

Class I Area: 

 Rainbow Lakes Wilderness 

Contact: Dale Higgins 

 Phone Number: (715) 762-5181 

 Fax Number: (715) 762-5179 

 Email Address: dhiggins@fs.fed.us 

 Mailing Address: 

 Chequamegon National Forest 

 1170 4th Avenue South 

 Park Falls, WI 54552 
180 

NATIONAL PARK SERVICE CLASS I AREAS 

For inquiries regarding routine permit issues, contact the NPS Air Resources Division in Lakewood, 

Colorado: John Bunyak, Chief, Policy, Planning and Permit Review Branch; (303) 969-2818; 

john_bunyak@nps.gov; P.O. Box 25287, Denver CO, 80225. 

ALASKA REGION

Denali National Park and Preserve 

Contact: Andrea Blakesley 

 Phone Number: (907) 683-2294 

 Fax Number: (907) 683-9612 

 Email Address: andrea_blakesley@nps.gov 

 Mailing Address: 

 P.O. Box 9 

 Denali Park, AK 99755 

INTERMOUNTAIN REGION

Arches National Park 

Contact: Superintendent 

 Phone Number: (801) 259-3911 

 Fax Number: (801) 259-8341 

 Mailing Address: 

 P.O. Box 907 

 Moab, UT 84532 

Bandelier National Monument 

Contact: Superintendent 

 Phone Number: (505) 672-3861 

 Fax Number: (505) 672-9607 

 Mailing Address: 

 HCR 1, Box 1, Suite 15 

 Los Alamos, NM 87544 

Big Bend National Park 

Contact: Superintendent 

 Phone Number: (915) 477-2251 

 Fax Number: (915) 477-2357 

 Mailing Address: 

 P.O. Box 129 

 Big Bend National Park, TX 79834 
181 

Black Canyon of the Gunnison National Park 

Contact: Superintendent 

 Phone Number: (970) 641-2337 

 Fax Number: (970) 641-2337 

 Mailing Address: 

 P.O. Box 1648 

 Montrose, CO 81402 

Bryce Canyon National Park 

Contact: Superintendent 

 Phone Number: (435) 834-5322 

 Fax Number: (435) 834-4102 

 Mailing Address: 

 P.O. Box 170001 

 Bryce Canyon, UT 84717 

Canyonlands National Park 

Contact: Superintendent 

 Phone Number: (801) 259-3911 

 Fax Number: (801) 259-8628 

 Mailing Address: 

 P.O. Box 907 

 Moab, UT 84532 

Capitol Reef National Park 

Contact: Superintendent 

 Phone Number: (801) 425-3791 

 Fax Number: (801) 425-3026 

 Mailing Address: 

 HC 70, Box 15 

 Torry, UT 84775 

Carlsbad Caverns National Park 

Contact: Superintendent 

 Phone Number: (505) 785-2232 

 Fax Number: (505) 785-2133 

 Mailing Address: 

 3225 National Parks Highway 

 Carlsbad, NM 88220 

Chiricahua National Monument 

Contact: Superintendent 

 Phone Number: (520) 824-3560 

 Fax Number: (520) 824-3421 

 Mailing Address: 

 Dos Cabezas Route, Box 6500 

 Willcox, AZ 85643 
182 

Glacier National Park 

Contact: Bill Michels 

 Phone Number: (406) 888-5441 

 Fax Number: (406) 888-7901 

 Email Address: bill_michels@nps.gov 

 Mailing Address: 

 P.O. Box 128 

 West Glacier, MT 59936 

Grand Canyon National Park 

Contact: Carl Bowman 

 Phone Number: (520) 638-7817 

 Fax Number: (520) 638-7797 

 Email Address: carl_bowman@nps.gov 

 Mailing Address: 

 P.O. Box 129 

 Grand Canyon, AZ 86023 

Grand Teton National Park 

Contact: Superintendent 

 Phone Number: (307) 739-3300 

 Fax Number: (307) 739-3438 

 Mailing Address: 

 P.O. Box 170 

 Moose, WY 83012 

Great Sand Dunes National Monument 

Contact: Superintendent 

 Phone Number: (719) 378-2312 

 Fax Number: (719) 378-2594 

 Mailing Address: 

 11500 Highway 150 

 Mosca, CO 81146 

Guadalupe Mountains National Park 

Contact: Superintendent 

 Phone Number: (915) 828-3251 

 Fax Number: (915) 828-3269 

 Mailing Address: 

 HC 60, Box 400 

 Salt Flat, TX 79847-9400 
183 

Mesa Verde National Park 

Contact: George San Miguel 

 Phone Number: (970) 529-4465 

 Fax Number: (970) 529- 4498 

 Email Address: george_sanmiguel@nps.gov 

 Mailing Address: 

 P.O. Box 8 

 Mesa Verde National Park, CO 81330 

Petrified Forest National Park 

Contact: Superintendent 

 Phone Number: (520) 524-6228 

 Fax Number: (520) 524-3567 

 Mailing Address: 

 Box 2217 

 Petrified Forest National Park, AZ 86028 

Rocky Mountain National Park 

Contact: Ken Czarnowski 

 Phone Number: (970) 586-1263 

 Fax Number: (970) 586-1310 

 Email Address: ken_czarnowski@nps.gov 

 Mailing Address: 

 Estes Park, CO 80517 

Saguaro National Park 

Contact: Meg Weesner 

 Phone Number: (520) 733-5170 

 Fax Number: (520) 733-5183 

 Email Address: meg_weesner@nps.gov 

 Mailing Address: 

 3693 South Old Spanish Trail 

 Tucson, AZ 85730-5601 

Yellowstone National Park 

Contact: Mary Hektner 

 Phone Number: (307) 344-2151 

 Fax Number: (307) 344-2323 

 Email Address: mary_hektner@nps.gov 

 Mailing Address: 

 P.O. Box 168 

 Yellowstone National Park, WY 82190 
184 

Zion National Park 

Contact: Jeff Bradybaugh 

 Phone Number: (801) 772-0140 

 Fax Number: (801) 772-3426 

 Email Address: jeff_bradybaugh@nps.gov 

 Mailing Address: 

 Springdale, UT 84767 

MIDWEST REGION

Badlands National Park 

Contact: Sandee Dingman 

 Phone Number: (605) 433-5262 

 Fax Number: (605) 433-5404 

 Email Address: sandee_dingman@nps.gov 

 Mailing Address: 

 P.O. Box 6 

 Interior, SD 57750 

Isle Royale National Park 

Contact: Superintendent 

 Phone Number: (906) 482-0986 

 Fax Number: (906) 482-7170 

 Mailing Address: 

 87 North Ripley Street 

 Houghton, MI 49931 

Theodore Roosevelt National Park 

Contact: Russell Runge 

 Phone Number: (701) 623-4466 

 Fax Number: (701) 623-4840 

 Email Address: russell_runge@nps.gov 

 Mailing Address: 

 P.O. Box 7 

 Medora, ND 58645 

Voyageurs National Park 

Contact: Roger Andrascik 

 Phone Number: (218) 283-9821 

 Fax Number: (218) 285-7407 

 Email Address: roger_andrascik@nps.gov 

 Mailing Address: 

 P.O. Box 50 

 International Falls, MN 56649 
185 

Wind Cave National Park 

Contact: Dan Roddy 

 Phone Number: (605) 745-1157 

 Fax Number: (605) 745-4207 

 Email Address: dan_roddy@nps.gov 

 Mailing Address: 

 RR 1, Box 190 

 Hot Springs, SD 57747 

NORTHEAST REGION

Acadia National Park 

Contact: Bob Breen 

 Phone Number: (207) 288-9561 

 Fax Number: (207) 288-5507 

 Email Address: bob_breen@nps.gov 

 Mailing Address: 

 P.O. Box 177 

 Bar Harbor, ME 04609 

Shenandoah National Park 

Contact: Christi Gordon 

 Phone Number: (540) 999-3499 

 Fax Number: (540) 999-3601 

 Email Address: christi_gordon@nps.gov 

 Mailing Address: 

 3655 U.S. Highway 211 East 

 Luray, VA 22835 

PACIFIC WEST REGION

Crater Lake National Park 

Contact: Superintendent 

 Phone Number: (541) 594-2211 

 Fax Number: (541) 584-2299 

 Mailing Address: 

 P.O. Box 7 

 Crater Lake, OR 97604 

Craters of the Moon National Monument 

Contact: Superintendent 

 Phone Number: (208) 527-3257 

 Fax Number: (208) 527-3073 

 Mailing Address: 

 P.O. Box 29 

 Arco, ID 83213 
186 

Haleakala National Park 

Contact: Superintendent 

 Phone Number: (808) 572-9306 

 Fax Number: (808) 572-1304 

 Mailing Address: 

 P.O. Box 369 

 Makawao, HI 96768 

Hawaii Volcanoes National Park 

Contact: Superintendent 

 Phone Number: (808) 985-6025 

 Fax Number: (808) 967-8186 

 Mailing Address: 

 P.O. Box 52 

 Volcanoes, HI 96718 

Joshua Tree National Park 

Contact: Chris Holbeck 

 Phone Number: (760) 367-5501 

 Fax Number: (760) 367-6392 

 Email Address: chris_holbeck@nps.gov 

 Mailing Address: 

 74485 National Monument Drive 

 Twentynine Palms, CA 92277 

Kings Canyon National Park 

Contact: Annie Esperanza 

 Phone Number: (559) 565-3341 

 Fax Number: (559) 565-3730 

 Email Address: annie_esperanza@nps.gov 

 Mailing Address: 

 47050 Generals Highway 

 Three Rivers, CA 93271 

Lassen Volcanic National Park 

Contact: Superintendent 

 Phone Number: (530) 595-4444 

 Fax Number: (530) 595-3262 

 Mailing Address: 

 P.O. Box 100 

 Mineral, CA 96063-0100 
187 

Lava Beds National Monument 

Contact: Chuck Barat 

 Phone Number: (530) 667-2282 

 Fax Number: (530) 667-2737 

 Email Address: chuck_barat@nps.gov 

 Mailing Address: 

 P.O. Box 867 

 Tulelake, CA 96134 

Mount Rainier National Park 

Contact: Barbara Samora 

 Phone Number: (360) 569-2177 x2301 

 Fax Number: (360) 569-2170 

 Email Address: barbara_samora@nps.gov 

 Mailing Address: 

 Tahoma Woods, Star Route 

 Ashford, WA 98304-9801 

North Cascades National Park 

Contact: Leigh Smith 

 Phone Number: (360) 856-5700 

 Fax Number: (360) 856-1934 

 Email Address: leigh_smith@nps.gov 

 Mailing Address: 

 2105 Highway 20 

 Sedro Woolley, WA 98284 

Olympic National Park 

Contact: Cat Hoffman 

 Phone Number: (360) 452-3011 

 Fax Number: (360) 452-0335 

 Email Address: cat_hoffman@nps.gov 

 Mailing Address: 

 600 East Park Avenue 

 Port Angeles, WA 98362 

Pinnacles National Monument 

Contact: Chad Moore 

 Phone Number: (408) 389-4485 

 Fax Number: (408) 389-4489 

 Email Address: chad_moore@nps.gov 

 Mailing Address: 

 5000 Highway 146 

 Paicines, CA 95043 
188 

Point Reyes National Seashore 

Contact: Superintendent 

 Phone Number: (415) 663-8522 

 Fax Number: (415) 663-8132 

 Mailing Address: 

 Point Reyes Station 

 Point Reyes, CA 94956 

Redwood National Park 

Contact: Superintendent 

 Phone Number: (707) 464-6101 

 Fax Number: (707) 464-1812 

 Mailing Address: 

 1111 Second Street 

 Crescent City, CA 95531 

Sequoia National Park 

Contact: Annie Esperanza 

 Phone Number: (559) 565-3341 

 Fax Number: (559) 565-3730 

 Email Address: annie_esperanza@nps.gov 

 Mailing Address: 

 47050 Generals Highway 

 Three Rivers, CA 93271 

Yosemite National Park 

Contact: Superintendent 

 Phone Number: (209) 372-0265 

 Fax Number: (209) 372-0220 

 Mailing Address: 

 P.O. Box 577 

 Yosemite National Park, CA 95389 

SOUTHEAST REGION

Everglades National Park 

Contact: Superintendent 

 Phone Number: (305) 242-7710 

 Fax Number: (305) 242-7728 

 Mailing Address: 

 P.O. Box 279 

 Homestead, FL 33030 
189 

Great Smoky Mountains National Park 

Contact: Jim Renfro 

 Phone Number: (423) 436-1708 

 Fax Number: (423) 436-1220 

 Email Address: jim_renfro@nps.gov 

 Mailing Address: 

 107 Park Headquarters Road 

 Gatlinburg, TN 37738 

Mammoth Cave National Park 

Contact: Bobby Carson 

 Phone Number: (502) 749-2508 

 Fax Number: (520) 749-2349 

 Email Address: bobby_carson@nps.gov 

 Mailing Address: 

 P.O. Box 7 

 Mammoth Cave, KY 42259 

Virgin Islands National Park 

Contact: Superintendent 

 Phone Number: (809) 775-6238 

 Fax Number: (809) 775-7025 

 Mailing Address: 

 6310 Estate Nazareth #10 

 St. Thomas, VI 00802 
190 

U.S. FISH AND WILDLIFE SERVICE CLASS I AREAS 

For inquiries regarding routine permit issues, contact the FWS Air Quality Branch in Lakewood, 

Colorado: Sandra Silva, Chief; (303) 969-2814; sandra_v_silva@nps.gov; P.O. Box 25287, Denver 

CO, 80225. 

 

 REGION 2

Bosque Del Apache Wilderness 

Contact: Refuge Manager 

 Phone Number: (505) 835-1828 

 Fax Number: (505) 835-0314 

 Mailing Address: 

 Bosque del Apache NWR 

 P.O. Box 1246 

 Socorro, NM 87801 

 

Salt Creek Wilderness

Contact: Refuge Manager 

 Phone Number: (505) 662-6755 

 Fax Number: (505) 623-9039 

 Mailing Address: 

 Bitter Lake NWR 

 P.O. Box 7 

 Roswell, NM 88202-0007 

Wichita Mountains Wilderness

Contact: Refuge Manager 

 Phone Number: (580) 429-3007 

 Fax Number: (580) 429-9323 

 Email Address: R2RW_WM@fws.gov 

 Mailing Address: 

 Wichita Mountains NWR 

 Rt. 1, Box 448 

 Indiahoma, OK 73552 

 

REGION 3

Seney Wilderness 

Contact: Refuge Manager 

 Phone Number: (906) 586-9851 

 Fax Number: (906)586-3800 

 Email Address: Mike_Tansy@fws.gov 

 Mailing Address: 

 Seney NWR 

 HCR 2, Box 1 

 Seney, MI 49883
191 

Mingo Wilderness 

Contact: Refuge Manager 

 Phone Number: (573) 222-3589 

 Fax Number: (573) 222-6343 

 Email Address: Gerald_Clawson@fws.gov 

 Mailing Address: 

 Mingo NWR 

 Route 1, Box 103 

 Puxico, MO 63960 

 

REGION 4

Breton Wilderness 

Contact: Refuge Manager 

 Phone Number: (504) 646-7555 

 Fax Number: (504) 646-7588 

 Email Address: howard_poitevint@fws.gov 

 Mailing Address: 

 Bogue Chitto NWR 

 1010 Gause Blvd., Bldg. 936 

 Slidell, LA 70458 

 

Cape Romain Wilderness 

Contact: Refuge Manager 

 Phone Number: (803) 928-3264 

 Fax Number: (803) 928-3803 

 Email Address: R4RW_SC.CRM@mail.fws.gov 

 Mailing Address: 

 Cape Romain NWR 

 5801 Highway 17 North 

 Awendaw, SC 29429 

 

Chassahowitzka Wilderness 

Contact: Refuge Manager 

 Phone Number: (352) 563-2088 

 Fax Number: (352) 795-7961 

 Mailing Address: 

 Chassahowitzka NWR 

 1502 S. Kings Bay Drive 

 Crystal River, FL 32629 
192 

Okefenokee Wilderness 

Contact: Refuge Manager 

 Phone Number: (912) 496-7366 

 Fax Number: (912) 496-7366 

 Mailing Address: 

 Okefenokee NWR 

 Route 2, Box 3330 

 Folkston, GA 31537 

St. Marks Wilderness 

Contact: Refuge Manager 

 Phone Number: (850) 925-6121 

 Fax Number: (850) 925-6930 

 Email Address: R4RW_FL.SMK@mail.fws.gov 

 Mailing Address: 

 St. Marks NWR 

 P.O. Box 68 

 St. Marks, FL 32355 

Swanquarter Wilderness 

Contact: Refuge Manager 

 Phone Number: (252) 926-4021 

 Fax Number: (252) 926-1743 

 Email Address: R4RW_NC.MTK@mail.fws.gov 

 Mailing Address: 

 Mattamuskeet NWR 

 Route 1, Box N-2 

 Swanquarter, NC 27885 

 

Wolf Island Wilderness 

Contact: Refuge Manager 

 Phone Number: (912) 652-4415 

 Fax Number: (912) 652-4385 

 Mailing Address: 

 Savannah Coastal Refuges 

 1000 Business Center Dr., Ste. 10 

 Savannah, GA 31405 

REGION 5

Brigantine Wilderness 

Contact: Refuge Manager 

 Phone Number: (609) 652-1665 

 Fax Number: (609) 652-1474 

 Email Address: R5RW_FBRNWR @fws.gov 

 Mailing Address: 

 Edwin B. Forsythe NWR 

 P.O. Box 72, Great Creek Rd. 

 Oceanville , NJ 08231 
193 

Moosehorn Wilderness 

Contact: Refuge Manager 

 Phone Number: (207) 454-3521 

 Fax Number: (207) 454-2550 

 Email Address: Mark_Sweeny@fws.gov 

 Mailing Address: 

 Moosehorn NWR 

 R.R. 1 Box 202, Suite 1 

 Baring, ME 04694-9703 

REGION 6

Lostwood Wilderness 

Contact: Refuge Manager 

 Phone Number: (701) 848-2722 

 Fax Number: (701) 848-2702 

 Mailing Address: 

 Lostwood NWR 

 R.R. 2 Box 98 

 Kenmare, ND 58746-9046 

Medicine Lake Wilderness 

Contact: Refuge Manager 

 Phone Number: (406) 789-2305 

 Fax Number: (406) 789-2350 

 Mailing Address: 

 Medicine Lake NWR 

 223 North Shore Road

 Medicine Lake, MT 59247 

Red Rock Lakes Wilderness 

Contact: Refuge Manager 

 Phone Number: (406) 276-3536 

 Fax Number: (406) 276-3538 

 Mailing Address: 

 Red Rock Lakes NWR 

 Monida Star Route, Box 15 

 Lima, MT 59739 

UL Bend Wilderness 

Contact: Refuge Manager 

 Phone Number: (406) 538-8706 

 Fax Number: (406) 538-7521 

 Mailing Address: 

 Charles M. Russell NWR 

 P.O. Box 110 

 Lewistown, MT 59457 
194 

 REGION 7

Bering Sea/Simeonof/Tuxedni Wilderness Areas 

Contact: Refuge Manager 

 Phone Number: (907) 235-6546 

 Fax Number: (907) 235-7783 

 Mailing Address: 

 Alaska Maritime NWR 

 2355 Kachemak Bay Drive, Suite 101 

 Homer, AK 99603 

 

 
195 

APPENDIX G. FLAG PARTICIPANTS 

The individuals listed in the attached table participated in the development of the FLAG Phase I 

Report. The abbreviations for the FLAG subgroup or committee on which participants served are 

shown below. 

LC = Leadership Committee 

CC = Coordinating Committee 

P = Policy Subgroup 

V = Visibility Subgroup 

O = Ozone Subgroup 

D = Deposition Subgroup 

T = Terminology (Glossary) Subgroup 
196 

 FLAG PARTICIPANTS 

Name Subgroup Organization Work Phone Fax Email Address 

 Acheson, Ann V Forest Service (406) 329-3493 (406) 329-3132 aacheson@fs.fed.us  Ahuja, Suraj O,V,D Forest Service (530) 934-3316 (530) 934-7384 sahuja@fs.fed.us  Bachman, Bob CC,V,D,T Forest Service (503) 808-2918 (503) 808-2973 rbachman@fs.fed.us  Bayle, Bruce P Forest Service (404) 347-3872 (404) 347-6197 bbayle@fs.fed.us 

∗Benoit, Clif V,P Forest Service -- -- -- 

 Blanchard, Karen EPA (919) 541-5503 (919) 541-5509 blanchard.karen@epamail.e

∗Blett, Tamara Forest Service -- -- -- 

 Boutcher, Steve Forest Service (503) 326-5434 (503) 808-2973 sboutcher@fs.fed.us  Bray, David T,V EPA (206) 553-4253 (206) 553-0110 bray.dave@epamail.epa.go

∗Breitenfeld, Dale Park Service -- -- -- 

 Bunyak, John P,T Park Service (303) 969-2818 (303) 969-2822 john_bunyak@nps.gov  Bytnerowicz, A. O Forest Service (909) 680-1562 (909) 680-1501 andrzej@deltanet.com 

∗Carriero, Joe CC,T Fish and Wildlife -- -- -- 

 Copeland, Scott V CIRA (CSU) (970) 491-3315 (970) 491-8598 COPELAND@CIRA.colo Fisher, Rich CC,V,P,O,T Forest Service (970) 498-1232 (970) 498-1010 rfisher@lamar.colostate.ed

∗Flores, Miguel P,O Park Service -- -- -- 

∗ No longer works for the agency, or now works for a different office. 
197 

Name Subgroup Organization Work Phone Fax Email Address 

 Haddow, Dennis P,V,T Forest Service (303) 275-5759 (303) 275-5754 dhaddow@fs.fed.us  Hogsett, Bill O EPA (541) 754-4632 (541) 754-4739 bill@heart.cor.epa.gov  Huber, Cindy V Forest Service (540) 265-5156 (540) 265-5145 chuber@fs.fed.us  Irwin, John V EPA (919) 541-5682 (919) 541-0044 irwin.john@epamail.epa.g Jackson, Bill O Forest Service (704) 257-4815 (704) 257-4263 bjacksono2@fs.fed.us  Lamb, Donna LC Forest Service (202) 205-0800 (202) 205-1096 dlamb@fs.fed.us  Malm, Bill V Park Service (970) 491-8292 (970) 491-8598 malm@CIRA.colostate.ed Maniero, Tonnie CC,O Park Service (303) 969-2806 (303) 969-2822 tonnie_maniero@nps.gov  Morris, Kristi Park Service (303) 987-6941 (303) 969-2822 kristi_morris@nps.gov  Morse, Dee CC,V Park Service (303) 969-2817 (303) 969-2822 dee_morse@nps.gov  Musselman, Bob O,D Forest Service (970) 498-1239 (970) 498-1010 bobm@lamar.colostate.edu  Notar, John V Park Service (303) 969-2079 (303) 969-2822 john_notar@nps.gov 

∗Parker, Kim D,O Forest Service -- -- -- 

 Peterson, Dave O BRD (206) 543-1587 (206) 695-0790 wild@u.washington.edu  Peterson, Janice O,D Forest Service (425) 744-3425 (425) 744-3255 jpeterson@fs.fed.us 

 Pitchford, Mark V NOAA (702) 895-0432 (702) 895-0507 MarcP@snsc.dri.edu  Pitt, Ken P USDA/OGC (303) 275-5539 (303) 275-5557 kenneth.pitt@usda.gov  Porter, Ellen CC,D Fish and Wildlife (303) 969-2617 (303) 969-2822 ellen_porter@nps.gov  Potter, Debby P,D Forest Service (505) 842-3143 (505) 842-3800 dapotter@fs.fed.us  Procter, Trent O Forest Service (559) 784-1500 (559) 781-4744 tprocter@fs.fed.us 

∗ No longer works for the agency or now works for a different office. 
198 

Name Subgroup Organization Work Phone Fax Email Address 

 Renfro, Jim O Park Service (423) 436-1708 (423) 436-5598 jim_renfro@nps.gov  Riebau, Al D Forest Service (202) 205-1524 (202) 205-1054 ariebau@fs.fed.us  Rocchio, Judy O Park Service (415) 427-1431 (415) 427-1487 judy_rocchio@nps.gov  Rolofson, Bud V Fish and Wildlife (303) 969-2804 (303) 969-2822 bud_rolofson@nps.gov  Scruggs, Mark V Park Service (303) 969-2077 (303) 969-2822 mark_scruggs@nps.gov  Shaver, Chris LC Park Service (303) 969-2074 (303) 969-2822 chris_shaver@nps.gov  Shepherd, Don Park Service (303) 969-2075 (303) 969-2822 don_shepherd@nps.gov  Silva, Sandra LC Fish and Wildlife (303) 969-2814 (303) 969-2822 sandra_silva@nps.gov  Stottlemyer, Bob D USGS/BRD (970) 498-1017 (970) 498-1010 crhoades@lamar.colostate Thomas, Jerome Forest Service (803) 561-4000 (803) 561-4004 jthomas@fs.fed.us 

∗Tonnessen, Kathy D Park Service -- -- -- 

 Vimont, John V Park Service (303) 969-2808 (303) 969-2822 john_vimont@nps.gov

∗ No longer works for the agency or now works for a different office. 
199 

APPENDIX H. BIBLIOGRAPHY 

Some of the documents cited below were referenced in this FLAG Phase I Report. Others are listed to 

provide background information. 

General References 

Adams, M.B., D.S. Nichols, C.A. Federer, K.F. Jensen and H. Parrott. 1991. Screening Procedure to 

Evaluate Effects of Air Pollution on Eastern Region Wildernesses Cited as Class I Air Quality Areas. 

General Technical Report NE-151. U.S. Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. Radnor, Pennsylvania. 

Binkley, D., C. Giardina, I. Dockersmith, D. Morse, M. Scruggs and K. Tonnessen. 1997. Status of Air 

Quality and Related Values in Class I National Parks and Monuments of the Colorado Plateau. U.S. 

Department of the Interior, National Park Service, Air Resources Division. Denver, Colorado. 

Blankenship, J.O., D.U. Potter, R.W. Fisher and J.M. Eilers. In Press. Guidelines for Evaluating Air 

Pollution Impacts on Class I Areas in the Southwestern Region. U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. Ft. Collins, Colorado. 

Bunyak, J. 1993. Permit Application Guidance for New Pollution Sources. Natural Resources Report 

NPS/NRAQD/NRR-93. U.S. Department of the Interior, National Park Service, Air Quality Division. 

Denver, Colorado. 

Eilers, J. M., C.L. Rose and T.J. Sullivan. 1994. Status of Air Quality and Effects of Atmospheric 

Pollutants on Ecosystems in the Pacific Northwest Region of the National Park Service. Technical 

Report NPS/NRAQD/NRTR-94/160. U.S. Department of the Interior, National Park Service, Air 

Quality Division. Denver, Colorado. 

Fox, D.G., A.M. Bartuska, J.G. Byrne, E. Cowling, R. Fisher, G.E. Likens, S.E. Lindberg, R.A. 

Linthurst, J. Messer and D.S. Nichols. 1989. A Screening Procedure to Evaluate Air Pollution Effects 

on Class I Wilderness Areas. General Technical Report RM-168. U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range Experiment Station. Ft. Collins, Colorado. 

Fox, D., G.J.C. Bernabo and B. Hood. 1987. Guidelines for Measuring the Physical, Chemical, and 

Biological Condition of Wilderness Ecosystems. General Technical Report RM-146. U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. 

Ft. Collins, Colorado. 

Garner, J.H.B., T. Pagano and E.B. Cowling. 1989. An Evaluation of the Role of Ozone, Acid 

Deposition, and Other Airborne Pollutants in the Forests of Eastern North America. General 

Technical Report SE-59. U.S. Department of Agriculture, Forest Service, Southeastern Forest 

Experiment Station. Asheville, North Carolina. 
200 

Haddow, D., R. Musselman, T. Blett and R. Fisher. 1998. Guidelines for Evaluating Air Pollution 

Impacts on Wilderness within the Rocky Mountain Region: Report of a Workshop, 1990. General 

Technical Report RMRS-GTR-4. U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station. Ft. Collins, Colorado. 

Ottmar, R. 1996. Linking recent historical and current forest vegetation patterns to smoke and 

crown fire in the Interior Columbia River Basin. Paper presented at the 13th Conference of Fire and 

Forest Meteorology, October 27-31, 1996. Lorne, Australia. 

Peterson, D.L., D.L. Schmoldt, J.M. Eilers, R.W. Fisher and R.D. Doty. 1993. Guidelines for 

Evaluating Air Pollution Impacts on Class I Wilderness Areas in California. General Technical 

Report PSW-GTR-136. U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station. Albany, California. 

Peterson, D.L., T.J. Sullivan, J.M. Eilers, S. Brace, D. Horner and K. Savig. 1998. Assessment of 

Air Quality and Air Pollutant Impacts in National Parks of the Rocky Mountains and Northern 

Great Plains. U.S. Department of the Interior, National Park Service, Air Resources Division. 

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